Comparing Full and Pre-Term Neonates' Heart Rate Variability in Rest Condition and during Spontaneous Interactions with Their Parents at Home.

BACKGROUND: Preterm neonates show decreased HRV compared to those at full-term. We compared HRV metrics between preterm and full-term neonates in transfer periods from neonate rest state to neonate-parent interaction, and vice versa. METHODS: Short-term recordings of the HRV parameters (time and frequency-domain indices and non-linear measurements) of 28 premature healthy neonates were compared with the metrics of 18 full-term neonates. HRV recordings were performed at home at term-equivalent age and HRV metrics were compared between the following transfer periods: from first rest state of the neonate (TI1) to a period in which the neonate interacted with the first parent (TI2), from TI2 to a second neonate rest state (TI3), and from TI3 to a period of neonate interaction with the second parent (TI4). RESULTS: For the whole HRV recording period, PNN50, NN50 and HF (%) was lower for preterm neonates compared to full-terms. These findings support the reduced parasympathetic activity of preterm compared to full-term neonates. The results of comparisons between transfer period simply a common coactivation of SNS and PNS systems for both full and pre-term neonates. CONCLUSIONS: Spontaneous interaction with the parent may reinforce both full and pre-term neonates' ANS maturation.

Review of Eye Tracking Metrics Involved in Emotional and Cognitive Processes.

Eye behaviour provides valuable information revealing one's higher cognitive functions and state of affect. Although eye tracking is gaining ground in the research community, it is not yet a popular approach for the detection of emotional and cognitive states. In this paper, we present a review of eye and pupil tracking related metrics (such as gaze, fixations, saccades, blinks, pupil size variation, etc.) utilized towards the detection of emotional and cognitive processes, focusing on visual attention, emotional arousal and cognitive workload. Besides, we investigate their involvement as well as the computational recognition methods employed for the reliable emotional and cognitive assessment. The publicly available datasets employed in relevant research efforts were collected and their specifications and other pertinent details are described. The multimodal approaches which combine eye-tracking features with other modalities (e.g. biosignals), along with artificial intelligence and machine learning techniques were also surveyed in terms of their recognition/classification accuracy. The limitations, current open research problems and prospective future research directions were discussed for the usage of eye-tracking as the primary sensor modality. This study aims to comprehensively present the most robust and significant eye/pupil metrics based on available literature towards the development of a robust emotional or cognitive computational model.

The interference of introversion-extraversion and depressive symptomatology with reasoning performance: a behavioural study.

The objective of this study was to investigate the link between the Eysenck Personality Questionnaire (EPQ) scores and depressive symptomatology with reasoning performance induced by a task including valid and invalid Aristotelian syllogisms. The EPQ and the Zung Depressive Scale (ZDS) were completed by 48 healthy subjects (27 male, 21 female) aged 33.5 ± 9.0 years. Additionally, the subjects engaged into two reasoning tasks (valid vs. invalid syllogisms). Analysis showed that the judgment of invalid syllogisms is a more difficult task than of valid judgments (65.1% vs. 74.6% of correct judgments respectively, p < 0.01). In both conditions, the subjects' degree of confidence is significantly higher when they make a correct judgment than when they make an incorrect judgment (83.8 ± 11.2 vs. 75.3 ± 17.3, p < 0.01). Subjects with extraversion as measured by EPQ and high sexual desire as rated by the relative ZDS subscale are more prone to make incorrect judgments in the valid syllogisms, while, at the same time, they are more confident in their responses. The effects of extraversion/introversion and sexual desire on the outcome measures of the valid condition are not commutative but additive. These findings indicate that extraversion/introversion and sexual desire variations may have a detrimental effect in the reasoning performance.

Circulating FGF21 vs. Stress Markers in Girls during Childhood and Adolescence, and in Their Caregivers: Intriguing Inter-Relations between Overweight/Obesity, Emotions, Behavior, and the Cared-Caregiver Relationship.

Fibroblast growth factor-21 (FGF21) acts on several brain regions, including the hypothalamic paraventricular nucleus, which is involved in the regulation of the hypothalamic-pituitary-adrenal (HPA) axis. The purpose of this study was to investigate the interrelations between FGF21 and stress indices in girls, as well as in their caregivers. 78 girls, aged between 5 and 15 years, were studied; 50 of them were overweight and obese (OB) and 28 in the control group (C). Serum FGF21 and hair and diurnal salivary cortisol were measured. Children participants filled in the Children's Depression Inventory (CDI) and the State-Trait Anxiety Inventory for Children (STAIC), while their caregivers filled in the State-Trait Anxiety Inventory (STAI), the Perceived Stress Scale (PSS), and the Holmes-Rahe Stress Events Scale (HRSES). The OB group girls had significantly higher levels of FGF21 than the C group (p < 0.001). In contrast to the C group, in whom FGF21 levels were positively correlated with both hair and salivary AUCg cortisol concentrations (p = 0.045 and p = 0.007, respectively), no such correlations were observed in the OB group. In the caregivers of the OB group, STAI-state (r = 0.388, p = 0.008), STAI-trait (r = 0.4, p = 0.006), PSS (r = 0.388, p = 0.008), and HRSES (r = 0.358, p = 0.015) scores, all correlated positively with the FGF21 levels of the children under their care. FGF21 concentrations positively correlated with hair and salivary cortisol levels in the C group only. These findings may represent an interesting correlation dictated by bi-directional empathy links between the primary caregivers and the children under their care.

The Effect of Pythagorean Self-Awareness on Heart Rate Variability, Perceived Stress and Behavior of Preschool Children.

Stress is associated with unhealthy habits and non-communicable diseases. It is also linked to communicable diseases due to its impact on immune function. These can be prevented through intervention programs in schools. The aim of this study was to examine the effect of the simplified Pythagorean Self-Awareness Intervention on heart rate variability (HRV) parameters, perceived stress and behaviors of preschool children. The sample of the study consisted of 45 preschool students. A "one group (double) pretest­posttest design" was used, to allow for comparisons of the measurements before and after the intervention. Students were assessed via two questionnaires ("Perceived Stress Scale for Children" (PSS-C) and "Checklist for Screening Behavioral Problems in Preschool Children") and a photoplethysmographic (PPG) device. The intervention lasted 9 weeks and included practicing of the Pythagorean Self-awareness techniques and the adoption of healthy behaviors. The results showed no statistically significant differences between the two pretests (p > 0.05 for all comparisons) and statistically significant differences between the second pretest and posttest ("Perceived Stress Scale for Children", (PSS-C) p < 0.0001, "Checklist for Screening Behavioral Problems in Preschool Children" p < 0.0001 and two indices of PPG device: heart rate mean, p < 0.0001, low frequency/very low frequency, p = 0.034). In conclusion, the Pythagorean Self-Awareness Intervention had a beneficial effect on the sample of preschool students examined, as the results showed an improvement in the perceived stress and the HRV parameters tested, and in engaging healthier behaviors, findings that indicate a relaxed psychologic state and a healthier lifestyle.

Stress, Inflammation and Metabolic Biomarkers Are Associated with Body Composition Measures in Lean, Overweight, and Obese Children and Adolescents.

The aim of this study was to examine the associations between multiple indices of stress, inflammation and metabolism vs. body composition parameters in 121 (43 boys, 78 girls) children and adolescents, aged 5-15 y. Subjects were divided into two groups: normal weight (N) (N = 40, BMI z-score = -0.1923 ± 0.6), and overweight/obese (OB) (N = 81, BMI z-score = 2.1947 ± 1.4). All subjects completed the State-Trait Anxiety Inventory for Children (STAIC) and Children's Depression Inventory, and underwent cortisol measurements in hair, diurnal series of saliva, and morning serum. Circulating concentrations of high sensitivity C-reactive protein (hsCRP) and other inflammation biomarkers were also obtained. Body composition analysis was performed with a clinically validated, advanced bioimpedance apparatus (BIA), while heart rate variability (HRV) was measured as a stress biomarker by photoplethysmography (PPG). The OB group had a higher STAIC-state score, waist-to-hip ratio, skeletal muscle mass, and total and abdominal fat mass, and a lower percent fat-free mass (FFM) and bone density than the N group. HRV did not differ between the groups. In the entire population, percent fat mass correlated strongly with circulating hsCRP (r = 0.397, p = 0.001), ferritin, and other inflammatory biomarkers, as well as with indices of insulin resistance. A strong correlation between serum hsCRP and hair cortisol was also observed (r = 0.777, p < 0.001), suggesting interrelation of chronic stress and inflammation. Thus, body fat accumulation in children and adolescents was associated with an elevation in clinical and laboratory biomarkers of stress, inflammation, and insulin resistance. BIA-ACC and PPG can be utilized as a direct screening tool for assessing overweight- and obesity -related health risks in children and adolescents.

Autonomic Nervous System Maturation and Emotional Coordination in Interactions of Preterm and Full-Term Infants With Their Parents: Protocol for a Multimethod Study.

BACKGROUND: There is limited knowledge on the physiological and behavioral pathways that may affect the developmental outcomes of preterm infants and particularly on the link between autonomic nervous system maturation and early social human behavior. Thus, this study attempts to investigate the way heart rate variability (HRV) parameters are related to emotional coordination in interactions of preterm and full-term infants with their parents in the first year of life and the possible correlation with the developmental outcomes of infants at 18 months. OBJECTIVE: The first objective is to investigate the relationship between emotional coordination and HRV in dyadic full-term infant-parent (group 1) and preterm infant-parent (group 2) interactions during the first postpartum year. The second objective is to examine the relationship of emotional coordination and HRV in groups 1 and 2 in the first postpartum year with the developmental outcomes of infants at 18 months. The third objective is to investigate the effect of maternal and paternal postnatal depression on the relation between emotional coordination and HRV in the two groups and on developmental outcomes at 18 months. The fourth objective is to examine the effect of family cohesion and coping on the relation between emotional coordination and HRV in the two groups and on developmental outcomes at 18 months. METHODS: This is an observational, naturalistic, and longitudinal study applying a mixed method design that includes the following: (1) video recordings of mother-infant and father-infant interactions at the hospital, in the neonatal period, and at home at 2, 4, 6, 9, and 12 months of the infants' life; (2) self-report questionnaires of parents on depressive symptoms, family cohesion, and dyadic coping of stress; (3) infants' HRV parameters in the neonatal period and at each of the above age points during and after infant-parent video recordings; and (4) assessment of toddlers' social and cognitive development at 18 months through an observational instrument. RESULTS: The study protocol has been approved by the Research Ethics Committee of the University of Crete (number/date: 170/September 18, 2020). This work is supported by the Special Account for Research Funds of the University of Crete (grant number: 10792-668/08.02.2021). All mothers (with their partners) of full-term and preterm infants who give birth between March 2021 and January 2022 at the General University Hospital of Crete (northern Crete, Greece) will be invited to participate. The researcher will invite the parents of infants to participate in the study 1 to 2 days after birth. Data collection is expected to be completed by March 2023, and the first results will be published by the end of 2023. CONCLUSIONS: Investigating the regulatory role of HRV and social reciprocity in preterm infants may have implications for both medicine and psychology. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/28089.

Abnormal auditory ERP N100 in children with dyslexia: comparison with their control siblings.

BACKGROUND: Recent research has implicated deficits of the working memory (WM) and attention in dyslexia. The N100 component of event-related potentials (ERP) is thought to reflect attention and working memory operation. However, previous studies showed controversial results concerning the N100 in dyslexia. Variability in this issue may be the result of inappropriate match up of the control sample, which is usually based exclusively on age and gender. METHODS: In order to address this question the present study aimed at investigating the auditory N100 component elicited during a WM test in 38 dyslexic children in comparison to those of 19 unaffected sibling controls. Both groups met the criteria of the International Classification of Diseases (ICD-10). ERP were evoked by two stimuli, a low (500 Hz) and a high (3000 Hz) frequency tone indicating forward and reverse digit span respectively. RESULTS: As compared to their sibling controls, dyslexic children exhibited significantly reduced N100 amplitudes induced by both reverse and forward digit span at Fp1, F3, Fp2, Fz, C4, Cz and F4 and at Fp1, F3, C5, C3, Fz, F4, C6, P4 and Fp2 leads respectively. Memory performance of the dyslexics group was not significantly lower than that of the controls. However, enhanced memory performance in the control group is associated with increased N100 amplitude induced by high frequency stimuli at the C5, C3, C6 and P4 leads and increased N100 amplitude induced by low frequency stimuli at the P4 lead. CONCLUSION: The present findings are in support of the notion of weakened capture of auditory attention in dyslexia, allowing for a possible impairment in the dynamics that link attention with short memory, suggested by the anchoring-deficit hypothesis.

Focal epileptic seizures anticipation based on patterns of heart rate variability parameters.

BACKGROUND AND OBJECTIVE: Heart rate variability parameters are studied by the research community as potential valuable indices for seizure detection and anticipation. This paper investigates heart activity abnormalities during focal epileptic seizures in childhood. METHODS: Seizures affect both the sympathetic and parasympathetic system which is expressed as abnormal patterns of heart rate variability (HRV) parameters. In the present study, a clinical dataset containing 42 focal seizures in long-term electrocardiographic (ECG) recordings from drug-resistant pediatric epileptic patients (with age 8.2 ±â€¯4.3 years) was analyzed. RESULTS: Results indicate that the time domain HRV parameters (heart rate, SDNN, standard deviation of heart rate, upper envelope) and spectral HRV parameters (LF/HF, normalized HF, normalized LF, total power) are significantly affected during ictal periods. The HRV features were ranked in terms of their relevance and efficacy to discriminate non-ictal/ictal periods and the top-ranked features were selected using the minimum Redundancy Maximum Relevance algorithm for further analysis. Then, a personalized anticipation algorithm based on multiple regression was introduced providing an "epileptic index" of imminent seizures. The performance of the system resulted in anticipation accuracy of 77.1% and an anticipation time of 21.8 s. CONCLUSIONS: The results of this analysis could permit the anticipation of focal seizures only using electrocardiographic signals and the implementation of seizure anticipation strategies for a range of real-life clinical applications.

Evidence of a posterior cingulate involvement (Brodmann area 31) in dyslexia: a study based on source localization algorithm of event-related potentials.

The study investigates the differences regarding the position of intracranial generators of P50 component of ERPs in 38 dyslexic children aged 11.47+/-2.12 years compared with their 19 healthy siblings aged 12.21+/-2.25. The dipoles were extracted by solving the inverse electromagnetic problem according to the recursively applied and projected multiple signal classification (RAP-MUSIC) algorithm approach. For improved localization of the main dipole the solutions were optimized using genetic algorithms. The statistical analysis revealed differences regarding the position of intracranial generators of low frequency of P50. Particularly, dyslexics showed main activity being located at posterior cingulate cortex (Brodmann's area 31) while controls exhibited main activity being located at retrosplenial cortex (Brodmann's area 30). These results may indicate a role for the posterior cingulate cortex in the pre-attentive processing operation of dyslexia beyond of its traditional function in terms of spatial attention and motor intention.

A computational platform for continuous seizure anticipation, monitoring and clinical evaluation.

The development of platforms that are able to continuously monitor and handle epileptic seizures in a non invasive manner is of great importance as they would improve the quality of life of drug resistant epileptic patients. In this work, a device and a computational platform is presented for acquiring low noise electroencephalographic signals, for the detection/prediction of epileptic seizures and the storage of ictal activity in an electronic personal health record. In order to develop this platform, a systematic clinical protocol was established including a number of drug resistant children from the University Hospital of Heraklion. Dry electrodes with innovative micro-spike design were proposed in order to increase the signal to noise ratio of the recorded EEG signals. A wearable low cost platform and its corresponding wireless communication protocol was developed focus on minimizing the interference with the patient's body. A computational subsystem with advanced algorithms provides detection/anticipation of upcoming seizure activity and aims to protect the patient from an accident due to a seizure or to improve his/her social life. Finally, the seizure activity information is stored in an electronic health record for further clinical evaluation.

Preattentive deficits in developmental disorders of scholastic skills.

Working memory deficiency has been implicated in developmental disorders of scholastic skills. The auditory P50 component of event-related potentials reflecting preattentive processing was investigated in 38 children with developmental disorders of scholastic skills and 19 sibling control children, as elicited during a working memory test. The P50 was evoked by two tones of low and high frequency (500 Hz and 3000 Hz). The group with developmental disorders of scholastic skills showed prolonged P50 latency induced by the low tone, located at the frontal area. The amplitude of P50 induced by the low tone exhibited significantly negative associations with both age and memory performance, whereas age and memory performance were associated positively. These findings indicate that preattentive processing deficits may be implicated not only in auditory cognition but also in developmental disorders of scholastic skills.

Detection of stress/anxiety state from EEG features during video watching.

This paper studies the effect of stress/anxiety states on EEG signals during video sessions. The levels of arousal and valence that are induced to each subject while watching each video are self rated. These levels are mapped in stress and relaxed states and subjects that fufill criteria of adequate anxiety/stress scale were chosen leading to a subset of 18 subjects. Then, temporal, spectral and non linear EEG features are evaluated for being able to represent accurately states under investigation. Feature selection schemes choose the most significant of them in order to provide increased discrimination ability between relaxed and anxiety/stress states.

An approach to absence epileptic seizures detection using Approximate Entropy.

Epilepsy is one of the most common chronic neurological diseases and the most common neurological chronic disease of childhood. The electroencephalogram (EEG) signal provides significant information neurologists take into consideration in the investigation and analysis of epileptic seizures. The Approximate Entropy (ApEn) is a formulated statistical parameter commonly used to quantify the regularity of a time series data of physiological signals. In this paper ApEn is used in order to detect the onset of epileptic seizures. The results show that the method provides promising results towards efficient detection of onset and ending of seizures, based on analyzing the corresponding EEG signals. ApEn parameters affect the method's behavior, suggesting that a more detailed study and a consistent methodology of their determination should be established. A preliminary analysis for the proper determination of these parameters is performed towards improving the results.

Absence seizure epilepsy detection using linear and nonlinear EEG analysis methods.

In this study, we investigated three measures capable of detecting absence seizures with increased sensitivity based on different underlying assumptions. Namely, an information-based method known as Approximate Entropy, a nonlinear alternative (Order Index), and a linear variance analysis approach. The results on the long-term EEG data suggest increased accuracy in absence seizure detection achieving sensitivity as high as 97.33% with no further application of any sophisticated classification scheme.

Detecting complexity abnormalities in dyslexia measuring Approximate Entropy of electroencephalographic signals.

Dyslexia constitutes a specific reading disability, a condition characterized by severe difficulty in the mastery of reading despite normal intelligence or adequate education. Electroencephalogram (EEG) signal may be able to play an important role in the diagnosis of dyslexia. The Approximate Entropy (ApEn) is a recently formulated statistical parameter used to quantify the regularity of a time series data of physiological signals. In this paper, we initially estimated the ApEn values in signals recorded from controls subjects and dyslectic children. These values were firstly used for the statistical analysis of the two groups and secondly as feature input in a classification scheme. We also used the cross-ApEn methodology to get a measure of the asynchrony of the signals recorded from different electrodes. This preliminary study provides promising results towards correct identification of dyslexic cases, analyzing the corresponding EEG signals.

Estimation of time-varying causal connectivity on EEG signals with the use of adaptive autoregressive parameters.

In this paper, we address the problem of time-varying causal connectivity estimators on Electro-encephalographic (EEG) signals by means of Directed Transfer Function (DTF). The DTF method reveals causal information flows between brain areas, while direct DTF (dDTF) is able to distinguish and estimate only direct flows. Since neuro-physiological signals such as EEG and event related potentials (ERP) can be nonstationary, their temporal dynamics cannot be satisfactorily represented. Time-varying dDTF can be estimated using Kalman Filter for adaptive calculation of multivariate autoregressive coefficients. This approach can reveal transient causal relations and model time-dependent flow patterns. This approach was applied to simulated signals and the results indicated that time-varying dDTF can provide efficient estimates of connectivity patterns.