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Background: The study of tactile perception during a childhood is extremely important for understanding the social and communicative aspects of the child's development. Tactile perception of stimuli with different valence can have different normative stages of development. Methods: In the present study, we examined changes in linear and nonlinear electroencephalogram (EEG) parameters during the presentation of pleasant (C-tactile optimal stroking), unpleasant (ice stroking), and neutral tactile stimuli in three groups of healthy volunteers: preschoolers 4 and 5 years, school-age children from 8 to 10 years, and adults from 20 to 40 years. Results: According to our findings, child maturation plays a significant role in the perception of pleasant and neutral tactile stimuli. Patterns of EEG dynamics related to tactile perception showed greater similarity between adult volunteers and school-aged children than preschoolers. Conclusions: Non-linear EEG parameters such as fractal dimension (FD), envelope mean frequency (EMF), and power spectral density (PSD) dynamics of the theta-rhythm were particularly sensitive to developmental changes in tactile perception. Hjorth complexity and peak alpha frequency (PAF) scores may serve as indicators of mature perception of C-tactile (CT)-stimuli. [ABSTRACT FROM AUTHOR]

Objective: The acoustic stimulation in consciousness patients may improve the diagnosis assessment and the effectiveness of rehabilitation procedures. We aimed to investigate the event-related potential (ERP) response to emotional auditory stimuli in comatose patients. Methods: We measured the nonlinear and linear electroencephalogram (EEG) features, prepared the acoustic analysis of stimuli parameters, and assessed the subjective emotional rates of stimuli characteristics. Results: Patients with better outcomes had recognizable ERP responses and significant changes of the nonlinear EEG features to emotional sounds, unlike patients with worse outcomes. The response of comatose patients was attributed to acoustical features of emotional sounds, whereas the EEG response of healthy subjects was associated with their subjective feelings. The comatose patients demonstrated the variable EEG activity for neutral and emotional sounds. Conclusion: Thus, the EEG reactivity followed the better outcome of comatose patients to emotional stimuli. The study assumed the substantial differences of emotional stimuli perception in the healthy and unconscious brain. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to determine the EEG changes induced by emotional non-verbal sounds using nonlinear signals' features and also to examine the subjective emotional response in patients with different neurological and psychiatric disorders. Methods: 141 subjects participated in our study: patients after moderate TBI, patients in acute coma, patients after stroke, patients with schizophrenia and controls. 7 types of emotionally charged stimuli were presented. Non-comatose participants were asked to assess the levels of experienced emotions. We analyzed fractal dimension, signal's envelope parameters and Hjorth mobility and complexity. Results: The Hjorth parameters were negatively correlated with irritation. The fractal dimension was positively correlated with arousal and empathy levels. The only presentation of laughter to post-stroke patients induced the reaction similar to the control group. Conclusions: The results showed that the investigated nonlinear features of resting state EEG are quite group-specific and also specific to the emotional state. Significance: The investigated features could serve to diagnose emotional impairments. [ABSTRACT FROM AUTHOR]

Objectives: Pupil dilation is controlled both by sympathetic and parasympathetic nervous system branches. We hypothesized that the dynamic of pupil size changes under cognitive load with additional false feedback can predict individual behavior along with heart rate variability (HRV) patterns and eye movements reflecting specific adaptability to cognitive stress. To test this, we employed an unsupervised machine learning approach to recognize groups of individuals distinguished by pupil dilation dynamics and then compared their autonomic nervous system (ANS) responses along with time, performance, and self-esteem indicators in cognitive tasks., Methods: Cohort of 70 participants were exposed to tasks with increasing cognitive load and deception, with measurements of pupillary dynamics, HRV, eye movements, and cognitive performance and behavioral data. Utilizing machine learning k-means clustering algorithm, pupillometry data were segmented to distinct responses to increasing cognitive load and deceit. Further analysis compared clusters, focusing on how physiological (HRV, eye movements) and cognitive metrics (time, mistakes, self-esteem) varied across two clusters of different pupillary response patterns, investigating the relationship between pupil dynamics and autonomic reactions., Results: Cluster analysis of pupillometry data identified two distinct groups with statistically significant varying physiological and behavioral responses. Cluster 0 showed elevated HRV, alongside larger initial pupil sizes. Cluster 1 participants presented lower HRV but demonstrated increased and pronounced oculomotor activity. Behavioral differences included reporting more errors and lower self-esteem in Cluster 0, and faster response times with more precise reactions to deception demonstrated by Cluster 1. Lifestyle variations such as smoking habits and differences in Epworth Sleepiness Scale scores were significant between the clusters., Conclusion: The differentiation in pupillary dynamics and related metrics between the clusters underlines the complex interplay between autonomic regulation, cognitive load, and behavioral responses to cognitive load and deceptive feedback. These findings underscore the potential of pupillometry combined with machine learning in identifying individual differences in stress resilience and cognitive performance. Our research on pupillary dynamics and ANS patterns can lead to the development of remote diagnostic tools for real-time cognitive stress monitoring and performance optimization, applicable in clinical, educational, and occupational settings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Alshanskaia, Portnova, Liaukovich and Martynova.)

Objective: We aimed to study the effects of EEG examination and ABA-therapy on resting-state EEG in children with low-functioning autism and tactile defensiveness., Methods: We have performed this study with three cohorts of preschoolers: children with autistic spectrum disorder (ASD) who needed applied behavior analysis (ABA) therapy due to their tactile defensiveness; children with ASD who didn't need ABA therapy; and the control group of healthy children. Number of microstates was determined in the initial and final parts of the resting-state EEGs., Results and Conclusions: Children with higher tactile defensiveness for the most part had specific EEG microstates associated with unpleasant emotions and senses. The EEG microstates of children with ASD who did not need ABA therapy, had more similarities with the EEG microstates of typically developing children except for temporary changes. Meanwhile, the children with tactile defensiveness demonstrated typical patterns of EEG microstates from start to finish of the procedure., Competing Interests: Conflict of interests: The authors have no conflicts of interest to disclose., (© 2020 the Author(s), licensee AIMS Press.)