Tonic Component Research Articles

The role of neuronal excitation and inhibition in the pre-Bötzinger complex on the cough reflex in the cat.

Brainstem respiratory neuronal network significantly contributes to cough motor pattern generation. Neuronal populations in the pre-Bötzinger complex (PreBötC) represent a substantial component for respiratory rhythmogenesis. We studied the role of PreBötC neuronal excitation and inhibition on mechanically induced tracheobronchial cough in 15 spontaneously breathing, pentobarbital anesthetized adult cats (35 mg/kg, iv initially). Neuronal excitation by unilateral microinjection of glutamate analog d,l-homocysteic acid resulted in mild reduction of cough abdominal electromyogram (EMG) amplitudes and very limited temporal changes of cough compared with effects on breathing (very high respiratory rate, high amplitude inspiratory bursts with a short inspiratory phase, and tonic inspiratory motor component). Mean arterial blood pressure temporarily decreased. Blocking glutamate-related neuronal excitation by bilateral microinjections of nonspecific glutamate receptor antagonist kynurenic acid reduced cough inspiratory and expiratory EMG amplitude and shortened most cough temporal characteristics similarly to breathing temporal characteristics. Respiratory rate decreased and blood pressure temporarily increased. Limiting active neuronal inhibition by unilateral and bilateral microinjections of GABAA receptor antagonist gabazine resulted in lower cough number, reduced expiratory cough efforts, and prolongation of cough temporal features and breathing phases (with lower respiratory rate). The PreBötC is important for cough motor pattern generation. Excitatory glutamatergic neurotransmission in the PreBötC is involved in control of cough intensity and patterning. GABAA receptor-related inhibition in the PreBötC strongly affects breathing and coughing phase durations in the same manner, as well as cough expiratory efforts. In conclusion, differences in effects on cough and breathing are consistent with separate control of these behaviors.NEW & NOTEWORTHY This study is the first to explore the role of the inspiratory rhythm and pattern generator, the pre-Bötzinger complex (PreBötC), in cough motor pattern formation. In the PreBötC, excitatory glutamatergic neurotransmission affects cough intensity and patterning but not rhythm, and GABAA receptor-related inhibition affects coughing and breathing phase durations similarly to each other. Our data show that the PreBötC is important for cough motor pattern generation, but cough rhythmogenesis appears to be controlled elsewhere.

34.5 THE EMOTIONAL OUTBURST INVENTORY (EMO-I): RATING WHAT KIDS DO WHEN THEY ARE IRRITABLE

Inadequate attention has been given to irritability’s tonic (persistently angry mood) vs phasic (outbursts of excessive temper with verbal or physical aggression) components or how one feels vs what one does. Most interviews do not make those distinctions; general rating scales address broadband aggression, although a few have a specific irritability factor. A good measure of outbursts (phasic irritability) and the impairment they cause is needed. The Emotional Outburst Inventory (EMO-I) is a brief screening tool developed for youth in clinical settings. It has 3 domains: outburst behaviors (up to 8, including swears, threatens, punches walls, throws things, hits/kicks), frequency (< monthly, weekly, daily), and duration (<15 minutes to more than 2 hours).

Validation of Gazepoint low-cost eye-tracking and psychophysiology bundle

Eye-tracking and recording of physiological signals are increasingly used in research within cognitive science and human–computer interaction. For example, gaze position and measures of autonomic arousal, including pupil dilation, skin conductance (SC), and heart rate (HR), provide an indicator of cognitive and physiological processes. The growing popularity of these techniques is partially driven by the emergence of low-cost recording equipment and the proliferation of open-source software for data collection and analysis of such signals. However, the use of new technology requires investigation of its reliability and validation with respect to real-world usage and against established technologies. Accordingly, in two experiments (total N = 69), we assessed the Gazepoint GP3-HD eye-tracker and Gazepoint Biometrics (GPB) system from Gazepoint. We show that the accuracy, precision, and robustness of the eye-tracker are comparable to competing systems. While fixation and saccade events can be reliably extracted, the study of saccade kinematics is affected by the low sampling rate. The GP3-HD is also able to capture psychological effects on pupil dilation in addition to the well-defined pupillary light reflex. Finally, moderate-to-strong correlations between physiological recordings and derived metrics of SC and HR between the GPB and the well-established BIOPAC MP160 support its validity. However, low amplitude of the SC signal obtained from the GPB may reduce sensitivity when separating phasic and tonic components. Similarly, data loss in pulse monitoring may pose difficulties for certain HR variability analyses.

Cortical monitoring of cardiac activity during rapid eye movement sleep: the heartbeat evoked potential in phasic and tonic rapid-eye-movement microstates.

Sleep is a fundamental physiological state that facilitates neural recovery during periods of attenuated sensory processing. On the other hand, mammalian sleep is also characterized by the interplay between periods of increased sleep depth and environmental alertness. Whereas the heterogeneity of microstates during non-rapid-eye-movement (NREM) sleep was extensively studied in the last decades, transient microstates during rapid-eye-movement (REM) sleep received less attention. REM sleep features two distinct microstates: phasic and tonic. Previous studies indicate that sensory processing is largely diminished during phasic REM periods, whereas environmental alertness is partially reinstated when the brain switches into tonic REM sleep. Here, we investigated interoceptive processing as quantified by the heartbeat evoked potential (HEP) during REM microstates. We contrasted the HEPs of phasic and tonic REM periods using two separate databases that included the nighttime polysomnographic recordings of healthy young individuals (N = 20 and N = 19). We find a differential HEP modulation of a late HEP component (after 500 ms post-R-peak) between tonic and phasic REM. Moreover, the late tonic HEP component resembled the HEP found in resting wakefulness. Our results indicate that interoception with respect to cardiac signals is not uniform across REM microstates, and suggest that interoceptive processing is partially reinstated during tonic REM periods. The analyses of the HEP during REM sleep may shed new light on the organization and putative function of REM microstates.

DIFFERENTIATION OF DICHOTOMOUS EMOTIONAL STATES IN ELECTRODERMAL ACTIVITY SIGNALS USING HIGHER-ORDER CROSSING FEATURES AND PARAMETRIC CLASSIFIERS

Prediction and recognition of happy and sad emotional states play important roles in many aspects of human life. In this work, an attempt has been made to classify them using Electrodermal Activity (EDA). For this, EDA signals are obtained from a public database and decomposed into tonic and phasic components. Features, namely Hjorth and higher-order crossing, are extracted from the phasic component of the signal. Further, these extracted features are fed to four parametric classifiers, namely, linear discriminant analysis, logistic regression, multilayer perceptron, and naive bayes for the classification. The results show that the proposed approach can classify the dichotomous happy and sad emotional states. The multilayer perceptron classifier is accurate (85.7%) in classifying happy and sad emotional states. The proposed method is robust in handling the dynamic variation of EDA signals for happy and sad emotional states. Thus, it appears that the proposed method could be able to understand the neurological, psychiatrical, and biobehavioural mechanisms of happy and sad emotional states.

Towards a model of arousal change after affective word pronunciation based on electrodermal activity and speech analysis

In this paper, we explore the possibility of building a model of subject arousal by exploiting the acquisition and the analysis of speech and electrodermal activity (EDA). Several issues have to be addressed to reach this goal as the estimation of the relationship between arousal and behavioral measures and the reliability of EDA signal during speech production. To accomplish this task, we will investigate the relation among EDA, speech activity and subject arousal, during isolated affective word pronunciation. Our results show that significant information on subject arousal can be obtained by analyzing EDA during the processing of out-of-context words with an emotional content in a reading aloud task. Based on a sample of eighteen Italian participants, we observed a significant relation between EDA features and self-reported arousal scores. Quantitative models relating EDA- and speech-derived features are proposed and discussed. We found that increasing values of tonic and phasic components of EDA signals correspond to increasing self-assessed arousal scores; Mel-frequency cepstral analysis of speech was also shown to carry relevant information about subject arousal, with a significant inverse relation to self-assessed scores. Our results suggest how the analysis of concurrent acquisition of EDA and speech features may offer a valid approach for the prediction of subject arousal during speech production, as well as a method for validating self-assessment ratings themselves.

Identification of Sympathetic Nervous System Activation From Skin Conductance: A Sparse Decomposition Approach With Physiological Priors.

Sweat secretions lead to variations in skin conductance (SC) signal. The relatively fast variation of SC, called the phasic component, reflects sympathetic nervous system activity. The slow variation related to thermoregulation and general arousal is known as the tonic component. It is challenging to decompose the SC signal into its constituents to decipher the encoded neural information related to emotional arousal. We model the phasic component using a second-order differential equation representing the diffusion and evaporation processes of sweating. We include a sparse impulsive neural signal that stimulates the sweat glands for sweat production. We model the tonic component with several cubic B-spline functions. We formulate an optimization problem with physiological priors on system parameters, a sparsity prior on the neural stimuli, and a smoothness prior on the tonic component. Finally, we employ a generalized-cross-validation-based coordinate descent approach to balance among the smoothness of the tonic component, the sparsity of the neural stimuli, and the residual. We illustrate that we can successfully recover the unknowns separating both tonic and phasic components from both experimental and simulated data (with ). Further, we successfully demonstrate our ability to automatically identify the sparsity level for the neural stimuli and the smoothness level for the tonic component. Our generalized-cross-validation-based novel method for SC signal decomposition successfully addresses previous challenges and retrieves a physiologically plausible solution. Accurate decomposition of SC could potentially improve cognitive stress tracking in patients with mental disorders.

An integrative method to quantitatively detect nocturnal motor seizures

In this proof-of-concept investigation, we demonstrate a marker-free video-based method to detect nocturnal motor seizures across a spectrum of motor seizure types, in a nighttime setting with a single adult female with refractory epilepsy. In doing so, we further explore the intermediate biosignals, visually mapping seizure “fingerprints” to seizure types. The method is designed to be flexible enough to generalize to unseen data, and shows promising performance characteristics for low-cost seizure detection and classification. The dataset contained recordings from 27 recorded nights. Seizure events were observed in 22 of these nights, with 36 unequivocally confirmed seizures. Each seizure was classified by an expert epileptologist according to both the ILAE 2017 standard and the Lüders semiological classification guidelines, yielding 5 of the ILAE-recognized seizure types and 7 distinct seizure semiologies. Evaluation was based on inference of motion, oscillation, and sound signals extracted from the recordings. The model architecture consisted of two feature extraction and event determination layers and one thresholding layer, establishing a simple framework for multimodal seizure analysis. Training of the optimal parameters was done by randomly resampling the event hits for each signal, and choosing a threshold that kept an expected 90 % sensitivity for the sample distribution. With the cut-off values selected, statistical performance was calculated for two target seizure groups: those containing a clonic component, and those containing a tonic component. When tuned to 90 % sensitivity, the system achieved a very low false discovery rate of 0.038/hour when targeting seizures with a clonic component, and a clinically-relevant rate of 1.02/hour when targeting seizures with a tonic component. These results indicate a sensitive method for detecting various nocturnal motor seizure types, and a high potential to differentiate motor seizures based on their video and audio signal characteristics. Paired with the low cost of this technique, both cost savings and improved quality of care might be achieved through further development and commercialization of this method.

Combination of instrumental and qualitative descriptive analysis for evaluation of selected tonic waters quality features.

The combination of sensory and instrumental analysis was applied for quality assurance of selected tonic waters. The quantitative descriptive analysis (QDA) in terms of 14 sensory attributes (aroma, astringency, bite, burn, numbing, tongue heaviness, carbonation, mouth coating, sweet taste, sour taste, bitter taste, sweet aftertaste, sour aftertaste, and bitter aftertaste) of selected tonic waters was performed by sensory experts. The results of this analysis were bound with potentiometric sensor results to elaborate mathematical models for prediction of these attributes by partial least squares (PLS) analysis. Predicted values of sensory attributes were in a good agreement with those obtained by sensory experts since the SD on predicted values were relatively low and determination coefficients were high. The only exception was for sweet aftertaste attribute, which model was not so well-fitted, probably due to specific interactions of tonic waters' sweet components. This approach may ensure the standards of food quality regarding sensory parameters with diminishing assessment's time and costs.

The α2/α3GABAA receptor modulator TPA023B alleviates not only the sensory but also the tonic affective component of chronic pain in mice.

Diminished synaptic inhibition in the spinal dorsal horn is a major contributor to pathological pain syndromes of neuropathic or inflammatory origin. Drugs that enhance the activity of dorsal horn α2/α3GABAARs normalize exaggerated nociceptive responses in rodents with neuropathic nerve lesions or peripheral inflammation but lack most of the typical side effects of less specific GABAergic drugs. It is however still unknown whether such drugs also reduce the clinically more relevant conscious perception of pain. Here, we investigated the effects of the α2/α3GABAAR subtype-selective modulator TPA023B on the tonic aversive component of pain in mice with peripheral inflammation or neuropathy. In neuropathic mice with a chronic constriction injury of the sciatic nerve, TPA023B not only reversed hyperalgesia to tactile and heat stimuli but also was highly effective in the conditioned place preference test. In the formalin test, TPA023B not only reduced licking of the injected paw but also reversed facial pain expression scores in the mouse grimace scale assay. Taken together, our results demonstrate that α2/α3GABAA receptor subtype-selective modulators not only reduce nociceptive withdrawal responses but also alleviate the tonic aversive components of chronic pain.

Spasmolytic Effects of Ageratum conyzoides in Vas Deferens

Premature ejaculation is a disorder that affects many men. This pathology may be the result of uncoordinated contraction of the vas deferens. Ageratum conyzoides is a plant used for the treatment of several pathologies in many regions in Brazil. Both in vitro and in vivo studies have shown that the A. conyzoides has many pharmacological properties, including a beneficial effect on benign prostatic hyperplasia, antitumoral effect and relaxation of gastrointestinal and genitourinary organs. The aim of the present study was to evaluate the effect of the A. conyzoides essential oil in the contractility of the vas deferens. 60-day old male Swiss mice were used in the experiment. Vas deferens were stimulated with potassium chlroride (KCl 80 mM), which induced a biphasic contractile response (phasic and tonic). The treated group had previous growing doses of the essential oil. The A. conyzoides induced the relaxation both of the phasic and tonic components, although the effect on the tonic component was statistically significant when compared to phasic. This inhibitory effect of the contractility may be potentially explored in order to guide clinical studies to treat premature ejaculation.

A simplified method for online extraction of skin conductance features: A pilot study on an immersive virtual-reality-based motor task.

There is a growing body of literature that recognizes the importance of Skin Conductance (SC) for assessing changes in emotional states, such as engagement to learning tasks, and its importance to estimate possible drawbacks affecting overall performance. To date, most of the commonly used methods for SC signal analysis, i.e. detecting its phasic and tonic components and thus extracting informative features, are either too simple and unreliable or too complex and thus inaccessible and inflexible, as well as unable to perform online analyses. The current work proposes a simplified but clear and effective algorithm based on a Machine State to search for expected behaviors in the well-defined morphology of the signal. Eleven (11) features were correctly extracted from 79 healthy subjects during an experimental setup for immersive virtual rehabilitation (balance study case). The method was also successfully applied as a tool to identify significant changes in the subjective psychophysiological response to different experimental conditions. These results point toward a potential role in virtual rehabilitation applications by getting real-time feedback in human-in-the-loop approaches.

Voice Reactivity as a Response to Acute Hypobaric Hypoxia at High Altitude.

BACKGROUND: Although the understanding of hypobaric hypoxia is increasing, it remains a hazard in aviation medicine. This study examined the feasibility of detecting voice markers sensitive to acute hypobaric hypoxia in an early presymptomatic (PRE-SYMP) stage.METHOD: Eight subjects qualified with hypobaric training completed a series of standardized speech tests in a hypobaric chamber at 20,000 ft and 25,000 ft (6096 and 7620 m) of altitude. Voice response patterns were analyzed in terms of fundamental frequency (F0), F0 range, and voice onset time (VOT). We hypothesized a PRE-SYMP compensatory stage in voice reactivity.RESULTS: There was a different dose-response reactivity course at 20,000 ft vs. 25,000 ft, nonlinear to altitude. At 20,000 ft, our hypothesis was confirmed. In comparison to sea level, a PRE-SYMP compensatory stage could be distinguished, characterized by a decreased F0 range, decreased VOT, and increased F0. During a transitional (TRANS) stage, in comparison with sea level, the F0-range reset, VOT decreased, and F0 increased. During a symptomatic (SYMP) stage, F0 increased, F0 range increased, and VOT decreased. At 25,000 ft, in comparison to sea level, voice reactivity showed increased F0 and F0 range and decreased VOT in a PRE-SYMP stage and increased F0 and F0 range in the SYMP stage.DISCUSSION: The compensatory PRE-SYMP stage is suggested to be the expression of ongoing bottom-up and top-down regulatory mechanisms, whereas the 25,000-ft results are interpreted as a combination of tonic and phasic voice reactivity. This tonic component needs to be foreseen in sea level baseline measures.Van Puyvelde M, Neyt X, Vanderlinden W, Van den Bossche M, Bucovaz T, De Winne T, Pattyn N. Voice reactivity as a response to acute hypobaric hypoxia at high altitude. Aerosp Med Hum Perform. 2020; 91(6):471-478.

Convolutional neural network based emotion classification using electrodermal activity signals and time-frequency features

In this work, an attempt has been made to classify emotional states using Electrodermal Activity (EDA) signals and Convolutional Neural Network (CNN) learned features. The EDA signals are obtained from the publicly available DEAP database and are decomposed into tonic and phasic components. The phasic component is subjected to the short-time Fourier transform. Thirty-eight features of time, frequency, and time–frequency domain are extracted from the phasic signal. These extracted features are applied to CNN to learn robust and prominent features. Five machine learning algorithms, namely linear discriminant analysis, multilayer perceptron, support vector machine, decision tree, and extreme learning machine are used for the classification. The results show that the proposed approach is able to classify the emotional states using arousal-valence dimensions. Classification using CNN learned features are found to be better than the conventional features. The trained end-to-end CNN model is found to be accurate (F-measure = 79.30% and 71.41% for arousal and valence dimensions) in classifying various emotional states. The proposed method is found to be robust in handling the dynamic variation of EDA signals for different emotional states. The results show that the proposed approach outperformed most of the state-of-the-art methods. Thus, it appears that the proposed method could be beneficial in analyzing various emotional states in both normal and clinical conditions.

Gender Differences in Tonic and Phasic Electrodermal Activity Components

Electrodermal activity (EDA) is a well-established psychophysiological measurement for research and clinical approaches. Males and females often display different physiological responses to stimuli, which can be detected by EDA recordings. Using a new method to measure skin conductance (SC), skin potential (SP) and skin susceptance (SS) simultaneously at the same electrode, these differences were investigated. SC, SP, and SS were recorded from 60 participants during relaxation and stress. It was found that both tonic and phasic EDA parameters indicated gender differences. In addition, females displayed greater tonic and phasic EDA parameters (except for skin potential responses (SPRs)) than males under both relaxation and conditions of stimulation (stress). However, these results were not statistically significant (p &gt; 0.05). This suggests that it is perhaps important to consider gender or at least note type of gender in EDA researches, but this cannot be generalized to clinical approaches.

Phytochemical Profile and Investigation of the Spasmolytic Activity of Hydroalcoholic Extract of Syzygium cumini (L.) Skeels Seeds

Aims: Perform the phytochemical analysis and investigate the spasmolytic activity of the hydroalcoholic extract obtained from S. cumini seeds (EHS-SC).&#x0D; Study Design: Qualitative phytochemical analysis and test of the EHS-SC on isolated smooth muscles (aorta, trachea, jejunum and uterus) of rat, to value effect relaxant and/or inhibitor.&#x0D; Place and Duration of Study: Pharmacognosy Laboratory II (Pharmacy course) and Pharmacology Research and Post-Graduate Laboratory (Department of Physiological Sciences) of the Federal University of Maranhão, between January 2017 and July 2018.&#x0D; Methodology: EHS-SC was submitted to phytochemical analysis and changes in color, fluorescence and absence or presence of precipitate were observed. The smooth muscle segments were suspended (tension of 1 g) in glass vats containing specific saline solution, at an appropriate temperature and after stabilization period, was stimulated by a suitable contractile agent to observe the effect of EHS-SC in the phasic and/or tonic component.&#x0D; Results: EHS-SC showed the majority presence of phenols, steroids, alkaloids and flavonoids (flavones, xanthones, flavonols) and was more potent in inhibiting phasic contractions induced by 10-6 M carbachol (CCh) in isolated rat jejunum (Emax: 83.5 ± 6.7%; n = 3). In addition, the EHS-SC (81.0; 243.0 and 729 µg/mL) antagonized the CCh effect (n = 4), increasing the EC50 (6.5 ± 1.3 x 10-7 M) of the CCh to 8.5 ± 1.1; 18.5 ± 3.4 and 40.5 ± 7.4 x 10-7 M and reducing the Emax (100%) of the CCh to 82.9 ± 10.5; 67.6 ± 6.0 and 10.1 ± 8.3%.&#x0D; Conclusion: Spasmolytic activity may be combined with antimicrobial and antidiarrheal activity according to literature data, where they show that the seeds have the same secondary metabolites, signaling the therapeutic potential for the treatment of colic and/or diarrhea.

Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review.

The electrodermal activity (EDA) signal is an electrical manifestation of the sympathetic innervation of the sweat glands. EDA has a history in psychophysiological (including emotional or cognitive stress) research since 1879, but it was not until recent years that researchers began using EDA for pathophysiological applications like the assessment of fatigue, pain, sleepiness, exercise recovery, diagnosis of epilepsy, neuropathies, depression, and so forth. The advent of new devices and applications for EDA has increased the development of novel signal processing techniques, creating a growing pool of measures derived mathematically from the EDA. For many years, simply computing the mean of EDA values over a period was used to assess arousal. Much later, researchers found that EDA contains information not only in the slow changes (tonic component) that the mean value represents, but also in the rapid or phasic changes of the signal. The techniques that have ensued have intended to provide a more sophisticated analysis of EDA, beyond the traditional tonic/phasic decomposition of the signal. With many researchers from the social sciences, engineering, medicine, and other areas recently working with EDA, it is timely to summarize and review the recent developments and provide an updated and synthesized framework for all researchers interested in incorporating EDA into their research.

The Unc13A isoform is important for phasic release and olfactory memory formation at mushroom body synapses

The cellular analysis of mushroom body (MB)-dependent memory forming processes is far advanced, whereas, the molecular and physiological understanding of their synaptic basis lags behind. Recent analysis of the Drosophila olfactory system showed that Unc13A, a member of the M(Unc13) release factor family, promotes a phasic, high release probability component, while Unc13B supports a slower tonic release component, reflecting their different nanoscopic positioning within individual active zones. We here use STED super-resolution microscopy of MB lobe synapses to show that Unc13A clusters closer to the active zone centre than Unc13B. Unc13A specifically supported phasic transmission and short-term plasticity of Kenyon cell:output neuron synapses, measured by combining electrophysiological recordings of output neurons with optogenetic stimulation. Knockdown of unc13A within Kenyon cells provoked drastic deficits of olfactory aversive short-term and anaesthesia-sensitive middle-term memory. Knockdown of unc13B provoked milder memory deficits. Thus, a low frequency domain transmission component is probably crucial for the proper representation of memory-associated activity patterns, consistent with sparse Kenyon cell activation during memory acquisition and retrieval. Notably, Unc13A/B ratios appeared highly diversified across MB lobes, leaving room for an interplay of activity components in memory encoding and retrieval.

Hydroalcoholic extract of leaves of Arrabidaea brachypoda (DC.) Bureau present antispasmodic activity mediated through calcium influx blockage

Aim: Since other species of the Bignoniaceae Family presented of antispasmodic activity, it was decided, by chemotaxonomic criterion, to determine the antispasmodic activity of the leaves of Arrabidaea brachypoda. Methodology: the segments of the rat jejunum were suspended in glass vats containing specific saline solution, at an appropriate temperature, and after stabilization period, were stimulated by a contractile agent to observe the inhibitory or relaxing effect of EHFAB. Results: EH-FAB showed the presence of 10 compounds, mainly rutin and it has an antispasmodic activity as it inhibits the phasic component and relaxes the tonic component of the contraction in isolated rat jejunum. To assess the mechanism of antispasmodic action, cumulative curves to the CCh were performed in which a non-competitive antagonism was observed, due to a displacement of the control curve to the right and reduction of the maximum contraction effect (Emax). Afterward, the participation of the calcium and/or potassium channels was evaluated by increasing the extracellular potassium, and it was observed that the EH-FAB relaxed the rat jejunum, suggesting the participation of the Ca2+ channels. To corroborate that hypothesis, the EH-FAB was tested against cumulative curves to Ca2+ in a free depolarizing solution of Ca2+, and it was observed that there was a shift of the curve to the right with a reduction in Emax. Conclusions: EH-FAB presents antispasmodic activity in isolated rat jejunum and it is suggested to block the influx of Ca2+ through voltage-gated calcium channels, signaling the therapeutic potential for the treatment of colic and/or diarrhea.

Towards Classifying Cognitive Performance by Sensing Electrodermal Activity in Children With Specific Learning Disorders

When children suffer from cognitive disorders, school performance and social environment are affected. Measuring changes in cognitive progress is essential for assessing the clinical follow-up of the patient's cognitive abilities. This process is considered as a challenge in ambulatory settings, where follow-ups should be non-invasive and continuous. Psychophysiological measures are an objective and unobtrusive evaluation alternative for recognizing cognitive changes. This paper aims to validate the relationship between cognition and the changes in physiological signals of children suffering from Specific Learning Disorders (SLD). This validation was carried out in an eHealth rehabilitation context (with the HapHop-Physio game). Electrodermal activity (EDA) signals were collected, processed, and analyzed through a machine learning approach. Obtained results were: a dataset built from wearable physiological data and a supervised classification model. The classification model can identify the children's cognitive performance (class) from the features of the tonic component of the EDA signal (attributes) with an accuracy of 79.95%. The presented results evidence that psychophysiological measures could allow for a highly objective follow-up for patients. They can also lead to creating a basis for further improvement of rehabilitation environments and developing neurofeedback applications.