Fractal Complexity in Spontaneous EEG Metastable-State Transitions: New Vistas on Integrated Neural Dynamics

Resting-state EEG signals undergo rapid transition processes (RTPs) that glue otherwise stationary epochs. We study the fractal properties of RTPs in space and time, supporting the hypothesis that the brain works at a critical state. We discuss how the global intermittent dynamics of collective excitations is linked to mentation, namely non-constrained non-task-oriented mental activity

Randomized Trial on the Effects of a Group EMDR Intervention on Narrative Complexity and Specificity of Autobiographical Memories: A Path Analytic and Supervised Machine-Learning Study

Narratives of autobiographical memories may be impaired by adverse childhood experiences, generating narrative fragmentation and increased levels of perceived distress. Eye movement desensitization and reprocessing (EMDR) proved to be an effective treatment to overcome traumatic experiences and to promote coherent autobiographical narratives. However, the specific mechanisms by which EMDR promotes narrative coherence remains largely unknown. We conducted a randomized controlled pilot trial (ClinicalTrials.gov Identifier NCT05319002) in a non-clinical sample of 27 children recruited in a primary school. Participants were randomly assigned to the experimental and control groups. The experimental group underwent a three-week group EMDR intervention. Subjective unit of distress (SUD), validity of cognition (VoC), classification of autobiographical memories, narrative complexity and specificity were assessed before and after the group EMDR intervention. The group EMDR intervention was able to improve SUD and VoC scales, narrative complexity and specificity, and promoted the classification of autobiographical memories as relational. The path analysis showed that SUD was able to predict VoC and narrative specificity, which, in turn, was able to predict both narrative complexity and the classification of autobiographical memories as relational. Machine-learning analysis showed that random tree classifier outperformed all other models by achieving a 93.33% accuracy. Clinical implications are discussed

Psychological intervention measures during the COVID-19 pandemic

The health emergency we are experiencing due to the spread of the COVID-19 disease has strongly influenced the psychological and physical health of the general population, including the health care professionals. The aim of this brief article is a preliminary analysis of the psychological interventions following the infectious disease outbreak in order to 1) implement guidelines for the existing emerging psychological crisis for people directly and indirectly affected by COVID-19, and 2) establish adequate procedures and prompt responses

Enhancing Qualities of Consciousness during Online Learning via Multisensory Interactions

Online-learning is a feasible alternative to in-person attendance during COVID-19 pan- demic. In this period, information technologies have allowed sharing experiences, but have also highlighted some limitations compared to traditional learning. Learning is strongly supported by some qualities of consciousness such as flow (intended as the optimal state of absorption and engagement activity) and sense of presence (feeling of exerting control, interacting with and get- ting immersed into real/virtual environments), behavioral, emotional, and cognitive engagement, together with the need for social interaction. During online learning, feelings of disconnection, social isolation, distractions, boredom, and lack of control exert a detrimental effect on the ability to reach the state of flow, the feeling of presence, the feeling of social involvement. Since online environments could prevent the rising of these learning–supporting variables, this article aims at describing the role of flow, presence, engagement, and social interactions during online sessions and at characterizing multisensory stimulations as a driver to cope with these issues. We argue that the use of augmented, mixed, or virtual reality can support the above-mentioned domains, and thus counteract the detrimental effects of physical distance. Such support could be further increased by enhancing multisensory stimulation modalities within augmented and virtual environme

A critical period for experience-dependent development of the feelings of safety during early infancy: A polyvagal perspective on anger and psychometric tools to assess perceived safety

Due to its distinct and widely recognizable pattern of face expression, anger has always been included in the repertoire of basic emotions (Ekman, 1999). Relying on polyvagal theory, Beauchaine et al. (2007) summarized the results of three studies (Beauchaine, 2001; Mead et al., 2004; Crowell et al., 2006) evaluating autonomic nervous system functioning in children manifesting aggression and conduct problems, aged 4–18. Children with aggressive oppositional defiant disorder or conduct disorder exhibited both sympathetic hypo-arousal at baseline and sympathetic insensitivity to reward at a very early age, marking a general disinhibitory tendency. In addition to this disinhibition, PNS deficiencies were found and contributed to increased emotional lability. Using transcutaneous vagus nerve stimulation (tVNS), Steenbergen et al. (2021), investigating subjects with age ranging from 18 to 28, found that active tVNS, compared to sham stimulation, enhanced the recognition of anger but reduced the ability to recognize sadness. According to developmental research, an actual expression of anger does not emerge until the last months of the first year of life (Sroufe, 1996). According to this, research on 5-, 12-, and 15-month-old infants has shown that an adult-like, late, non-linear pattern of cortical response to masked faces at various levels of visibility emerged as early as 5 months of age, starting around 900 ms, possibly due to the development of the right fusiform gyrus (Guy et al., 2016) and its increased sensitivity to fearful faces from 5 to 12 months (Xie et al., 2019; Chen et al., 2021). Subsequently, this late component shifted to a more sustained and faster response in older infants (~750 ms), to reach around 300 ms in adults (Kouider et al., 2013). Consequently, in infants aged 5–12 months exposed to facial expressions of happiness, fear, and anger with normal levels of visibility, the N290 event-related potential (ERP) component was found to be larger in amplitude in response to angry and happy faces than to angry ones, revealing greater cortical activation in the right fusiform face area, while the P400 and the negative-central (Nc) ERP components were found to be larger in amplitude in response to angry faces than to happy and fearful ones, revealing greater activation of the posterior cingulate cortex (PCC)/precuneus associated with the allocation of infants' attention. Interestingly, these effects emerged at 5 months, became well established at 7 months, and then disappeared at 12 months (Xie et al., 2019; Chen et al., 2021). As extensively shown for sensory development (Berardi et al., 2003; Hübener and Bonhoeffer, 2014; Ribot et al., 2021), this evidence may suggest a sensitive period for emotional development (Woodard and Pollak, 2020) related, in particular, to the learning of safety (Porges, 2015, 2022)

Moving Auto-Correlation Window Approach for Heart Rate Estimation in Ballistocardiography Extracted by Mattress-Integrated Accelerometers

Continuous heart monitoring is essential for early detection and diagnosis of cardiovascular diseases, which are key factors for the evaluation of health status in the general population. Therefore, in the future, it will be increasingly important to develop unobtrusive and transparent cardiac monitoring technologies for the population. The possible approaches are the development of wearable technologies or the integration of sensors in daily-life objects. We developed a smart bed for monitoring cardiorespiratory functions during the night or in the case of continuous monitoring of bedridden patients. The mattress includes three accelerometers for the estimation of the ballistocardiogram (BCG). BCG signal is generated due to the vibrational activity of the body in response to the cardiac ejection of blood. BCG is a promising technique but is usually replaced by electrocardiogram due to the difficulty involved in detecting and processing the BCG signals. In this work, we describe a new algorithm for heart parameter extraction from the BCG signal, based on a moving auto-correlation sliding-window. We tested our method on a group of volunteers with the simultaneous co-registration of electrocardiogram (ECG) using a single-lead configuration. Comparisons with ECG reference signals indicated that the algorithm performed satisfactorily. The results presented demonstrate that valuable cardiac information can be obtained from the BCG signal extracted by low cost sensors integrated in the mattress. Thus, a continuous unobtrusive heart-monitoring through a smart bed is now feasible

Fast regulation of vertical squat jump during push-off in skilled jumpers

The height of a maximum Vertical Squat Jump (VSJ) reflects the useful power produced by a jumper during the push-off phase. In turn this partly depends on the coordination of the jumper's segmental rotations at each instant. The physical system constituted by the jumper has been shown to be very sensitive to perturbations and furthermore the movement is realized in a very short time (ca. 300 ms), compared to the timing of known feedback loops. However, the dynamics of the segmental coordination and its efficiency in relation to energetics at each instant of the push-off phase still remained to be clarified. Their study was the main purpose of the present research. Eight young adult volunteers (males) performed maximal VSJ. They were skilled in jumping according to their sport activities (track and field or volleyball). A video analysis on the kinematics of the jump determined the influence of the jumpers' segments rotation on the vertical velocity and acceleration of the body mass center (MC). The efficiency in the production of useful power at the jumpers' MC level, by the rotation of the segments, was measured in consequence. The results showed a great variability in the segmental movements of the eight jumpers, but homogeneity in the overall evolution of these movements with three consecutive types of coordination in the second part of the push-off (lasting roughly 0.16 s). Further analyses gave insights on the regulation of the push-off, suggesting that very fast regulation(s) of the VSJ may be supported by: (a) the adaptation of the motor cerebral programming to the jumper's physical characteristics; (b) the control of the initial posture; and (c) the jumper's perception of the position of his MC relative to the ground reaction force, during push-off, to reduce energetic losses

A Machine Learning Approach Unveils the Relationships between Sickness Behavior and Interoception after Vaccination: Suggestions for Psychometric Indices of Higher Vulnerability

Objective: Prior research has suggested a possible connection between vaccination and manifestations of Sickness Behavior; however, a need remains to first delve deeper into this association and second examine how Interoceptive Awareness and emotional factors may modulate individuals’ perceptions of their health status post vaccination. Method: An online retrospective cross-sectional survey of 647 individuals who received a COVID-19 vaccination was conducted. Together with vaccination side effects, socio-demographic characteristics, health status, level of concern about vaccination, and Interoceptive Awareness were collected at the baseline level. Mood, sleep, and Sickness Behavior were assessed at baseline and after vaccination. Data were analyzed using inferential statistics and machine learning techniques. Results: After vaccination, there was a significant increase in Sickness Behavior levels (mean (±SD) SicknessQ T0 = 1.57 (±2.72), mean (±SD) SicknessQ T1 = 5.54 (±5.51); p-value = 0.001; ES = 0.77). A Machine Learning analysis revealed specific patterns of individual dispositions (sex and age), baseline emotional characteristics (levels of depression, anxiety, stress, and concern about adverse reactions), as well as some components of Interoceptive Awareness (Noticing, Body Listening, and Attention Regulation), as predictors of high levels of Sickness Behavior, both in terms of overall scores (JRIP: 72.65% accuracy, AUC = 0.692, d = 0.709; F1 = 0.726) and individual items (JRIP: 75.77% accuracy, AUC = 0.694; d = 0.717; F1 = 0.754). Conclusions: Our results provide new insight into post-immune reactions by highlighting the contribution of Interoceptive Awareness in modulating the severity of Sickness Behavior. This sheds light on the role of awareness of bodily sensations in modulating perceptions of health status, helping to identify the characteristics that make individuals more prone to feeling sick

Scaling and intermittency of brain events as a manifestation of consciousness

We discuss the critical brain hypothesis and its relationship with intermittent renewal processes displaying power-law decay in the distribution of waiting times between two consecutive renewal events. In particular, studies on complex systems in a "critical" condition show that macroscopic variables, integrating the activities of many individual functional units, undergo fluctuations with an intermittent serial structure characterized by avalanches with inverse-power-law (scale-free) distribution densities of sizes and inter-event times. This condition, which is denoted as "fractal intermittency", was found in the electroencephalograms of subjects observed during a resting state wake condition. It remained unsolved whether fractal intermittency correlates with the stream of consciousness or with a non-task-driven default mode activity, also present in non-conscious states, like deep sleep. After reviewing a method of scaling analysis of intermittent systems based of event-driven random walks, we show that during deep sleep fractal intermittency breaks down, and re-establishes during REM (Rapid Eye Movement) sleep, with essentially the same anomalous scaling of the pre-sleep wake condition. From the comparison of the pre-sleep wake, deep sleep and REM conditions we argue that the scaling features of intermittent brain events are related to the level of consciousness and, consequently, could be exploited as a possible indicator of consciousness in clinical applications

Sleep slow oscillations favour local cortical plasticity underlying the consolidation of reinforced procedural learning in human sleep

We investigated changes of slow-wave activity and sleep slow oscillations in the night following procedural learning boosted by reinforcement learning, and how these changes correlate with behavioural output. In the Task session, participants had to reach a visual target adapting cursor's movements to compensate an angular deviation introduced experimentally, while in the Control session no deviation was applied. The task was repeated at 13:00 hours, 17:00 hours and 23:00 hours before sleep, and at 08:00 hours after sleep. The deviation angle was set at 15° (13:00 hours and 17:00 hours) and increased to 45° (reinforcement) at 23:00 hours and 08:00 hours. Both for Task and Control nights, high-density electroencephalogram sleep recordings were carried out (23:30-19:30 hours). The Task night as compared with the Control night showed increases of: (a) slow-wave activity (absolute power) over the whole scalp; (b) slow-wave activity (relative power) in left centro-parietal areas; (c) sleep slow oscillations rate in sensorimotor and premotor areas; (d) amplitude of pre-down and up states in premotor regions, left sensorimotor and right parietal regions; (e) sigma crowning the up state in right parietal regions. After Task night, we found an improvement of task performance showing correlations with sleep slow oscillations rate in right premotor, sensorimotor and parietal regions. These findings suggest a key role of sleep slow oscillations in procedural memories consolidation. The diverse components of sleep slow oscillations selectively reflect the network activations related to the reinforced learning of a procedural visuomotor task. Indeed, areas specifically involved in the task stand out as those with a significant association between sleep slow oscillations rate and overnight improvement in task performance