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When assessing trainees' progresses during a driving training program, instructors can only rely on the evaluation of a trainee's explicit behavior and their performance, without having any insight about the training effects at a cognitive level. However, being able to drive does not imply knowing how to drive safely in a complex scenario such as the road traffic. Indeed, the latter point involves mental aspects, such as the ability to manage and allocate one's mental effort appropriately, which are difficult to assess objectively. In this scenario, this study investigates the validity of deploying an electroencephalographic neurometric of mental effort, obtained through a wearable electroencephalographic device, to improve the assessment of the trainee. The study engaged 22 young people, without or with limited driving experience. They were asked to drive along five different but similar urban routes, while their brain activity was recorded through electroencephalography. Moreover, driving performance, subjective and reaction times measures were collected for a multimodal analysis. In terms of subjective and performance measures, no driving improvement could be detected either through the driver's subjective measures or through their driving performance. On the other side, through the electroencephalographic neurometric of mental effort, it was possible to catch their improvement in terms of mental performance, with a decrease in experienced mental demand after three repetitions of the driving training tasks. These results were confirmed by the analysis of reaction times, that significantly improved from the third repetition as well. Therefore, being able to measure when a task is less mentally demanding, and so more automatic, allows to deduce the degree of users training, becoming capable of handling additional tasks and reacting to unexpected events.
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Conducción de Automóvil , Dispositivos Electrónicos Vestibles , Humanos , Adolescente , Tiempo de Reacción , Electroencefalografía/métodos , Accidentes de TránsitoRESUMEN
Fatigued driving is one of the main causes of traffic accidents. The electroencephalogram (EEG)-based mental state analysis method is an effective and objective way of detecting fatigue. However, as EEG shows significant differences across subjects, effectively "transfering" the EEG analysis model of the existing subjects to the EEG signals of other subjects is still a challenge. Domain-Adversarial Neural Network (DANN) has excellent performance in transfer learning, especially in the fields of document analysis and image recognition, but has not been applied directly in EEG-based cross-subject fatigue detection. In this paper, we present a DANN-based model, Generative-DANN (GDANN), which combines Generative Adversarial Networks (GAN) to enhance the ability by addressing the issue of different distribution of EEG across subjects. The comparative results show that in the analysis of cross-subject tasks, GDANN has a higher average accuracy of 91.63% in fatigue detection across subjects than those of traditional classification models, which is expected to have much broader application prospects in practical brain-computer interaction (BCI).
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Algoritmos , Interfaces Cerebro-Computador , Electroencefalografía , Humanos , Aprendizaje Automático , Redes Neurales de la ComputaciónRESUMEN
The sample size is a crucial concern in scientific research and even more in behavioural neurosciences, where besides the best practice it is not always possible to reach large experimental samples. In this study we investigated how the outcomes of research change in response to sample size reduction. Three indices computed during a task involving the observations of four videos were considered in the analysis, two related to the brain electroencephalographic (EEG) activity and one to autonomic physiological measures, i.e., heart rate and skin conductance. The modifications of these indices were investigated considering five subgroups of sample size (32, 28, 24, 20, 16), each subgroup consisting of 630 different combinations made by bootstrapping n (n = sample size) out of 36 subjects, with respect to the total population (i.e., 36 subjects). The correlation analysis, the mean squared error (MSE), and the standard deviation (STD) of the indexes were studied at the participant reduction and three factors of influence were considered in the analysis: the type of index, the task, and its duration (time length). The findings showed a significant decrease of the correlation associated to the participant reduction as well as a significant increase of MSE and STD (p < 0.05). A threshold of subjects for which the outcomes remained significant and comparable was pointed out. The effects were to some extents sensitive to all the investigated variables, but the main effect was due to the task length. Therefore, the minimum threshold of subjects for which the outcomes were comparable increased at the reduction of the spot duration.
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Electroencefalografía , Neurociencias , Frecuencia Cardíaca , Humanos , Tamaño de la MuestraRESUMEN
The capability of monitoring user's performance represents a crucial aspect to improve safety and efficiency of several human-related activities. Human errors are indeed among the major causes of work-related accidents. Assessing human factors (HFs) could prevent these accidents through specific neurophysiological signals' evaluation but laboratory sensors require highly-specialized operators and imply a certain grade of invasiveness which could negatively interfere with the worker's activity. On the contrary, consumer wearables are characterized by their ease of use and their comfortability, other than being cheaper compared to laboratory technologies. Therefore, wearable sensors could represent an ideal substitute for laboratory technologies for a real-time assessment of human performances in ecological settings. The present study aimed at assessing the reliability and capability of consumer wearable devices (i.e., Empatica E4 and Muse 2) in discriminating specific mental states compared to laboratory equipment. The electrooculographic (EOG), electrodermal activity (EDA) and photoplethysmographic (PPG) signals were acquired from a group of 17 volunteers who took part to the experimental protocol in which different working scenarios were simulated to induce different levels of mental workload, stress, and emotional state. The results demonstrated that the parameters computed by the consumer wearable and laboratory sensors were positively and significantly correlated and exhibited the same evidences in terms of mental states discrimination.
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Laboratorios , Dispositivos Electrónicos Vestibles , Frecuencia Cardíaca , Humanos , Reproducibilidad de los Resultados , Carga de TrabajoRESUMEN
Current telemedicine and remote healthcare applications foresee different interactions between the doctor and the patient relying on the use of commercial and medical wearable sensors and internet-based video conferencing platforms. Nevertheless, the existing applications necessarily require a contact between the patient and sensors for an objective evaluation of the patient's state. The proposed study explored an innovative video-based solution for monitoring neurophysiological parameters of potential patients and assessing their mental state. In particular, we investigated the possibility to estimate the heart rate (HR) and eye blinks rate (EBR) of participants while performing laboratory tasks by mean of facial-video analysis. The objectives of the study were focused on: (i) assessing the effectiveness of the proposed technique in estimating the HR and EBR by comparing them with laboratory sensor-based measures and (ii) assessing the capability of the video-based technique in discriminating between the participant's resting state (Nominal condition) and their active state (Non-nominal condition). The results demonstrated that the HR and EBR estimated through the facial-video technique or the laboratory equipment did not statistically differ (p > 0.1), and that these neurophysiological parameters allowed to discriminate between the Nominal and Non-nominal states (p < 0.02).
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Frecuencia Cardíaca , Telemedicina , Grabación en Video , Adulto , Parpadeo , Femenino , Humanos , MasculinoRESUMEN
Human tissues own conductive properties, and the electrical activity produced by human organs can propagate throughout the body due to neuro transmitters and electrolytes. Therefore, it might be reasonable to hypothesize correlations and similarities between electrical activities among different parts of the body. Since no works have been found in this direction, the proposed study aimed at overcoming this lack of evidence and seeking analogies between the brain activity and the electrical activity of non-cerebral locations, such as the neck and wrists, to determine if i) cerebral parameters can be estimated from non-cerebral sites, and if ii) non-cerebral sensors can replace cerebral sensors for the evaluation of the users under specific experimental conditions, such as eyes open or closed. In fact, the use of cerebral sensors requires high-qualified personnel, and reliable recording systems, which are still expensive. Therefore, the possibility to use cheaper and easy-to-use equipment to estimate cerebral parameters will allow making some brain-based applications less invasive and expensive, and easier to employ. The results demonstrated the occurrence of significant correlations and analogies between cerebral and non-cerebral electrical activity. Furthermore, the same discrimination and classification accuracy were found in using the cerebral or non-cerebral sites for the user's status assessment.
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Ondas Encefálicas/fisiología , Encéfalo/fisiología , Conductividad Eléctrica , Procesamiento de Señales Asistido por Computador , Adulto , Electroencefalografía , Mano/fisiología , Humanos , Aprendizaje Automático , Cuello/fisiología , Adulto JovenRESUMEN
One century after the first recording of human electroencephalographic (EEG) signals, EEG has become one of the most used neuroimaging techniques. The medical devices industry is now able to produce small and reliable EEG systems, enabling a wide variety of applications also with no-clinical aims, providing a powerful tool to neuroscientific research. However, these systems still suffer from a critical limitation, consisting in the use of wet electrodes, that are uncomfortable and require expertise to install and time from the user. In this context, dozens of different concepts of EEG dry electrodes have been recently developed, and there is the common opinion that they are reaching traditional wet electrodes quality standards. However, although many papers have tried to validate them in terms of signal quality and usability, a comprehensive comparison of different dry electrode types from multiple points of view is still missing. The present work proposes a comparison of three different dry electrode types, selected among the main solutions at present, against wet electrodes, taking into account several aspects, both in terms of signal quality and usability. In particular, the three types consisted in gold-coated single pin, multiple pins and solid-gel electrodes. The results confirmed the great standards achieved by dry electrode industry, since it was possible to obtain results comparable to wet electrodes in terms of signals spectra and mental states classification, but at the same time drastically reducing the time of montage and enhancing the comfort. In particular, multiple-pins and solid-gel electrodes overcome gold-coated single-pin-based ones in terms of comfort.
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Encéfalo/fisiología , Electroencefalografía/métodos , Adulto , Área Bajo la Curva , Artefactos , Electrodos , Oro/química , Humanos , Aprendizaje Automático , Masculino , Curva ROC , Plata/química , Dispositivos Electrónicos VestiblesRESUMEN
Aberrant alternative splicing events play a critical role in cancer biology, contributing to tumor invasion, metastasis, epithelial-mesenchymal transition, and drug resistance. Recent studies have shown that alternative splicing is a key feature for transcriptomic variations in colorectal cancer, which ranks third among malignant tumors worldwide in both incidence and mortality. Long non-coding RNAs can modulate this process by acting as trans-regulatory agents, recruiting splicing factors, or driving them to specific targeted genes. LncH19 is a lncRNA dis-regulated in several tumor types and, in colorectal cancer, it plays a critical role in tumor onset, progression, and metastasis. In this paper, we found, that in colorectal cancer cells, the long non-coding RNA H19 can bind immature RNAs and splicing factors as hnRNPM and RBFOX2. Through bioinformatic analysis, we identified 57 transcripts associated with lncH19 and containing binding sites for both splicing factors, hnRNPM, and RBFOX2. Among these transcripts, we identified the mRNA of the GTPase-RAC1, whose alternatively spliced isoform, RAC1B, has been ascribed several roles in the malignant transformation. We confirmed, in vitro, the binding of the splicing factors to both the transcripts RAC1 and lncH19. Loss and gain of expression experiments in two colorectal cancer cell lines (SW620 and HCT116) demonstrated that lncH19 is required for RAC1B expression and, through RAC1B, it induces c-Myc and Cyclin-D increase. In vivo, investigation from biopsies of colorectal cancer patients showed higher levels of all the explored genes (lncH19, RAC1B, c-Myc and Cyclin-D) concerning the healthy counterpart, thus supporting our in vitro model. In addition, we identified a positive correlation between lncH19 and RAC1B in colorectal cancer patients. Finally, we demonstrated that lncH19, as a shuttle, drives the splicing factors RBFOX2 and hnRNPM to RAC1 allowing exon retention and RAC1B expression. The data shown in this paper represent the first evidence of a new mechanism of action by which lncH19 carries out its functions as an oncogene by prompting colorectal cancer through the modulation of alternative splicing.
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Empalme Alternativo , Neoplasias Colorrectales , Regulación Neoplásica de la Expresión Génica , Factores de Empalme de ARN , ARN Largo no Codificante , Proteína de Unión al GTP rac1 , Humanos , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/patología , Neoplasias Colorrectales/metabolismo , ARN Largo no Codificante/genética , Proteína de Unión al GTP rac1/genética , Proteína de Unión al GTP rac1/metabolismo , Factores de Empalme de ARN/genética , Factores de Empalme de ARN/metabolismo , Línea Celular Tumoral , Ribonucleoproteína Heterogénea-Nuclear Grupo M/metabolismo , Ribonucleoproteína Heterogénea-Nuclear Grupo M/genética , Proteínas Represoras/genética , Proteínas Represoras/metabolismoRESUMEN
Despite the proven effectiveness of cochlear implant (CI) in the hearing restoration of deaf or hard-of-hearing (DHH) children, to date, extreme variability in verbal working memory (VWM) abilities is observed in both unilateral and bilateral CI user children (CIs). Although clinical experience has long observed deficits in this fundamental executive function in CIs, the cause to date is still unknown. Here, we have set out to investigate differences in brain functioning regarding the impact of monaural and binaural listening in CIs compared with normal hearing (NH) peers during a three-level difficulty n-back task undertaken in two sensory modalities (auditory and visual). The objective of this pioneering study was to identify electroencephalographic (EEG) marker pattern differences in visual and auditory VWM performances in CIs compared to NH peers and possible differences between unilateral cochlear implant (UCI) and bilateral cochlear implant (BCI) users. The main results revealed differences in theta and gamma EEG bands. Compared with hearing controls and BCIs, UCIs showed hypoactivation of theta in the frontal area during the most complex condition of the auditory task and a correlation of the same activation with VWM performance. Hypoactivation in theta was also observed, again for UCIs, in the left hemisphere when compared to BCIs and in the gamma band in UCIs compared to both BCIs and NHs. For the latter two, a correlation was found between left hemispheric gamma oscillation and performance in the audio task. These findings, discussed in the light of recent research, suggest that unilateral CI is deficient in supporting auditory VWM in DHH. At the same time, bilateral CI would allow the DHH child to approach the VWM benchmark for NH children. The present study suggests the possible effectiveness of EEG in supporting, through a targeted approach, the diagnosis and rehabilitation of VWM in DHH children.
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Estimulación Acústica , Percepción Auditiva , Implantación Coclear , Implantes Cocleares , Electroencefalografía , Memoria a Corto Plazo , Personas con Deficiencia Auditiva , Percepción Visual , Humanos , Niño , Femenino , Implantación Coclear/instrumentación , Masculino , Personas con Deficiencia Auditiva/rehabilitación , Personas con Deficiencia Auditiva/psicología , Estudios de Casos y Controles , Ritmo Teta , Estimulación Luminosa , Ritmo Gamma , Adolescente , Percepción del Habla , Corrección de Deficiencia Auditiva/instrumentación , Corteza Cerebral/fisiopatología , Corteza Cerebral/fisiología , Sordera/fisiopatología , Sordera/rehabilitación , Sordera/cirugía , AudiciónRESUMEN
MicroRNAs (miRNAs) are small non-coding ribonucleic acids (RNAs) that play a role in many regulatory pathways in eukaryotes. They usually exert their functions by binding mature messenger RNAs. The prediction of the binding targets of the endogenous miRNAs is crucial to unravel the processes they are involved in. In this work, we performed an extensive miRNA binding sites (MBS) prediction over all the annotated transcript sequences and made them available through an UCSC track. MBS annotation track allows to study and visualize the human miRNA binding sites transcriptome-wide in a genome browser, together with any other available information the user is interested in. In the creation of the database that underlies the MBS track, three consolidated algorithms of miRNA binding prediction have been used: PITA, miRanda and TargetScan, and information about the binding sites predicted by all of them has been collected. MBS track displays high-confident miRNA binding sites for the whole length of each human transcript, both coding and non-coding ones. Each annotation can redirect to a web page with the details of the miRNA binding and the involved transcripts. MBS can be easily applied to retrieve specific information such as the effects of alternative splicing on miRNA binding or when a specific miRNA binds an exon-exon junction in the mature RNA. Overall, MBS will be of great help for studying and visualizing, in a user-friendly mode, the predicted miRNA binding sites on all the transcripts arising from a gene or a region of interest. Database URL https://datasharingada.fondazionerimed.com:8080/MBS.
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MicroARNs , Transcriptoma , Humanos , Transcriptoma/genética , MicroARNs/genética , MicroARNs/metabolismo , Algoritmos , Genoma , Sitios de UniónRESUMEN
Nowadays, fostered by technological progress and contextual circumstances such as the economic crisis and pandemic restrictions, remote education is experiencing growing deployment. However, this growth has generated widespread doubts about the actual effectiveness of remote/online learning compared to face-to-face education. The present study was aimed at comparing face-to-face and remote education through a multimodal neurophysiological approach. It involved forty students at a driving school, in a real classroom, experiencing both modalities. Wearable devices to measure brain, ocular, heart and sweating activities were employed in order to analyse the students' neurophysiological signals to obtain insights into the cognitive dimension. In particular, four parameters were considered: the Eye Blink Rate, the Heart Rate and its Variability and the Skin Conductance Level. In addition, the students filled out a questionnaire at the end to obtain an explicit measure of their learning performance. Data analysis showed higher cognitive activity, in terms of attention and mental engagement, in the in-presence setting compared to the remote modality. On the other hand, students in the remote class felt more stressed, particularly during the first part of the lesson. The analysis of questionnaires demonstrated worse performance for the remote group, thus suggesting a common "disengaging" behaviour when attending remote courses, thus undermining their effectiveness. In conclusion, neuroscientific tools could help to obtain insights into mental concerns, often "blind", such as decreasing attention and increasing stress, as well as their dynamics during the lesson itself, thus allowing the definition of proper countermeasures to emerging issues when introducing new practices into daily life.
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Cigarette smoking impairs the lung innate immune response making smokers more susceptible to infections and severe symptoms. Dysregulation of cell death is emerging as a key player in chronic inflammatory conditions. We have recently reported that short exposure of human monocyte-derived macrophages (hMDMs) to cigarette smoke extract (CSE) altered the TLR4-dependent response to lipopolysaccharide (LPS). CSE caused inhibition of the MyD88-dependent inflammatory response and activation of TRIF/caspase-8/caspase-1 pathway leading to Gasdermin D (GSDMD) cleavage and increased cell permeability. Herein, we tested the hypothesis that activation of caspase-8 by CSE increased pro-inflammatory cell death of LPS-stimulated macrophages. To this purpose, we measured apoptotic and pyroptotic markers as well as the expression/release of pro-inflammatory mediators in hMDMs exposed to LPS and CSE, alone or in combination, for 6 and 24 h. We show that LPS/CSE-treated hMDMs, but not cells treated with CSE or LPS alone, underwent lytic cell death (LDH release) and displayed apoptotic features (activation of caspase-8 and -3/7, nuclear condensation, and mitochondrial membrane depolarization). Moreover, the negative regulator of caspase-8, coded by CFLAR gene, was downregulated by CSE. Activation of caspase-3 led to Gasdermin E (GSDME) cleavage. Notably, lytic cell death caused the release of the damage-associated molecular patterns (DAMPs) heat shock protein-60 (HSP60) and S100A8/A9. This was accompanied by an impaired inflammatory response resulting in inhibited and delayed release of IL6 and TNF. Of note, increased cleaved caspase-3, higher levels of GSDME and altered expression of cell death-associated genes were found in alveolar macrophages of smoker subjects compared to non-smoking controls. Overall, our findings show that CSE sensitizes human macrophages to cell death by promoting pyroptotic and apoptotic pathways upon encountering LPS. We propose that while the delayed inflammatory response may result in ineffective defenses against infections, the observed cell death associated with DAMP release may contribute to establish chronic inflammation. CS exposure sensitizes human macrophages to pro-inflammatory cell death. Upon exposure to LPS, CS inhibits the TLR4/MyD88 inflammatory response, downregulating the pro-inflammatory genes TNF and IL6 and the anti-apoptotic gene CFLAR, known to counteract caspase-8 activity. CS enhances caspase-8 activation through TLR4/TRIF, with a partial involvement of RIPK1, resulting on the activation of caspase-1/GSDMD axis leading to increased cell permeability and DAMP release through gasdermin pores [19]. At later timepoints caspase-3 becomes strongly activated by caspase-8 triggering apoptotic events which are associated with mitochondrial membrane depolarization, gasdermin E cleavage and secondary necrosis with consequent massive DAMP release.
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Fumar Cigarrillos , Enfermedad Pulmonar Obstructiva Crónica , Humanos , Proteínas Adaptadoras del Transporte Vesicular/metabolismo , Caspasa 3/metabolismo , Caspasa 8/metabolismo , Muerte Celular , Gasderminas , Interleucina-6/metabolismo , Lipopolisacáridos/farmacología , Lipopolisacáridos/metabolismo , Macrófagos/metabolismo , Factor 88 de Diferenciación Mieloide/metabolismo , Nicotiana/metabolismo , Receptor Toll-Like 4/genética , Receptor Toll-Like 4/metabolismoRESUMEN
Statistical tests of differential expression usually suffer from two problems. Firstly, their statistical power is often limited when applied to small and skewed data sets. Secondly, gene expression data are usually discretized by applying arbitrary criteria to limit the number of false positives. In this work, a new statistical test obtained from a convolution of multivariate hypergeometric distributions, the Hy-test, is proposed to address these issues. Hy-test has been carried out on transcriptomic data from breast and kidney cancer tissues, and it has been compared with other differential expression analysis methods. Hy-test allows implicit discretization of the expression profiles and is more selective in retrieving both differential expressed genes and terms of Gene Ontology. Hy-test can be adopted together with other tests to retrieve information that would remain hidden otherwise, e.g., terms of (1) cell cycle deregulation for breast cancer and (2) "programmed cell death" for kidney cancer.
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Neoplasias de la Mama , Neoplasias Renales , Neoplasias de la Mama/genética , Femenino , Perfilación de la Expresión Génica/métodos , Ontología de Genes , Humanos , Neoplasias Renales/genética , Modelos EstadísticosRESUMEN
Human errors are widely considered among the major causes of road accidents. Furthermore, it is estimated that more than 90% of vehicle crashes causing fatal and permanent injuries are directly related to mental tiredness, fatigue, and drowsiness of the drivers. In particular, driving drowsiness is recognized as a crucial aspect in the context of road safety, since drowsy drivers can suddenly lose control of the car. Moreover, the driving drowsiness episodes mostly appear suddenly without any prior behavioral evidence. The present study aimed at characterizing the onset of drowsiness in car drivers by means of a multimodal neurophysiological approach to develop a synthetic electroencephalographic (EEG)-based index, able to detect drowsy events. The study involved 19 participants in a simulated scenario structured in a sequence of driving tasks under different situations and traffic conditions. The experimental conditions were designed to induce prominent mental drowsiness in the final part. The EEG-based index, so-called "MDrow index", was developed and validated to detect the driving drowsiness of the participants. The MDrow index was derived from the Global Field Power calculated in the Alpha EEG frequency band over the parietal brain sites. The results demonstrated the reliability of the proposed MDrow index in detecting the driving drowsiness experienced by the participants, resulting also more sensitive and timely sensible with respect to more conventional autonomic parameters, such as the EyeBlinks Rate and the Heart Rate Variability, and to subjective measurements (self-reports).
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Technologies like passive brain-computer interfaces (BCI) can enhance human-machine interaction. Anyhow, there are still shortcomings in terms of easiness of use, reliability, and generalizability that prevent passive-BCI from entering real-life situations. The current work aimed to technologically and methodologically design a new gel-free passive-BCI system for out-of-the-lab employment. The choice of the water-based electrodes and the design of a new lightweight headset met the need for easy-to-wear, comfortable, and highly acceptable technology. The proposed system showed high reliability in both laboratory and realistic settings, performing not significantly different from the gold standard based on gel electrodes. In both cases, the proposed system allowed effective discrimination (AUC > 0.9) between low and high levels of workload, vigilance, and stress even for high temporal resolution (<10 s). Finally, the generalizability of the proposed system has been tested through a cross-task calibration. The system calibrated with the data recorded during the laboratory tasks was able to discriminate the targeted human factors during the realistic task reaching AUC values higher than 0.8 at 40 s of temporal resolution in case of vigilance and workload, and 20 s of temporal resolution for the stress monitoring. These results pave the way for ecologic use of the system, where calibration data of the realistic task are difficult to obtain.
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The driving drowsiness has been identified as one of the major causes of road traffic accidents, causing fatalities and permanent injuring. Drowsy drivers are prone to suddenly lose control of the car, mostly without any prior behavioral cue. The present study involved 19 participants in a simulated driving protocol, designed to induce mental drowsiness into the drivers. The objective of the study consisted in testing an innovative Electroencephalographic (EEG)-based index, the MDrow index, in detecting the driving drowsiness. Such an index, derived from parietal EEG channels, was already validated in our previous work achieving outstanding performance with respect to more conventional techniques. In this study, the possibility of obtaining a similar index from the frontal sites in order to foster its exploitation in real environments has been investigated. The results demonstrated the capability of the "frontal" MDrow index in evaluating the driving drowsiness experienced by the participants with performance comparable to that one previously validated over parietal sites. Also, the impact of the reduction of the electrodes number on index reliability has been investigated, in order to evaluate its compatibility with current wearable EEG devices.
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Conducción de Automóvil , Fases del Sueño , Electroencefalografía/métodos , Humanos , Reproducibilidad de los Resultados , VigiliaRESUMEN
This pilot study investigates the neurophysiological patterns of visual and auditory verbal working memory (VWM) in unilateral cochlear implant users (UCIs). We compared the task-related electroencephalogram (EEG) power spectral density of 7- to 13-year-old UCIs (n = 7) with a hearing control group (HC, n = 10) during the execution of a three-level n-back task with auditory and visual verbal (letters) stimuli. Performances improved as memory load decreased regardless of sensory modality (SM) and group factors. Theta EEG activation over the frontal area was proportionally influenced by task level; the left hemisphere (LH) showed greater activation in the gamma band, suggesting lateralization of VWM function regardless of SM. However, HCs showed stronger activation patterns in the LH than UCIs regardless of SM and in the parietal area (PA) during the most challenging audio condition. Linear regressions for gamma activation in the PA suggest the presence of a pattern-supporting auditory VWM only in HCs. Our findings seem to recognize gamma activation in the PA as the signature of effective auditory VWM. These results, although preliminary, highlight this EEG pattern as a possible cause of the variability found in VWM outcomes in deaf children, opening up new possibilities for interdisciplinary research and rehabilitation intervention.
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Driver's stress affects decision-making and the probability of risk occurrence, and it is therefore a key factor in road safety. This suggests the need for continuous stress monitoring. This work aims at validating a stress neurophysiological measure-a Neurometric-for out-of-the-lab use obtained from lightweight EEG relying on two wet sensors, in real-time, and without calibration. The Neurometric was tested during a multitasking experiment and validated with a realistic driving simulator. Twenty subjects participated in the experiment, and the resulting stress Neurometric was compared with the Random Forest (RF) model, calibrated by using EEG features and both intra-subject and cross-task approaches. The Neurometric was also compared with a measure based on skin conductance level (SCL), representing one of the physiological parameters investigated in the literature mostly correlated with stress variations. We found that during both multitasking and realistic driving experiments, the Neurometric was able to discriminate between low and high levels of stress with an average Area Under Curve (AUC) value higher than 0.9. Furthermore, the stress Neurometric showed higher AUC and stability than both the SCL measure and the RF calibrated with a cross-task approach. In conclusion, the Neurometric proposed in this work proved to be suitable for out-of-the-lab monitoring of stress levels.
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Training assessment is usually done by evaluating information derived from instructor's supervision related to the pilot's operational performance and behavior. However, this approach lacks objective measures, especially regarding the pilots' mental states while accomplishing the flight training tasks. The study therefore aimed at developing and testing a method for gathering and analyzing in real-time pilots' brain activity and skin conductance to improve the training evaluation. In this regard, Novice pilots' neurophysiological signals were acquired throughout multi-crew training sessions. The results demonstrated how the methodology proposed was able to endow real-time pilots' mental workload and arousal assessment for i) better evaluating training progress and operational behavior during the training session, and ii) for objectively comparing different training sessions.
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Nivel de Alerta , Carga de Trabajo , NeurofisiologíaRESUMEN
In several fields, the need for a joint analysis of brain activity and eye activity to investigate the association between brain mechanisms and manifest behavior has been felt. In this work, two levels of attentional demand, elicited through a conjunction search task, have been modelled in terms of eye blinks, brain activity, and brain network features. Moreover, the association between endogenous neural mechanisms underlying attentional demand and eye blinks, without imposing a time-locked structure to the analysis, has been investigated. The analysis revealed statistically significant spatial and spectral modulations of the recorded brain activity according to the different levels of attentional demand, and a significant reduction in the number of eye blinks when a higher amount of attentional investment was required. Besides, the integration of information coming from high-density electroencephalography (EEG), brain source localization, and connectivity estimation allowed us to merge spectral and causal information between brain areas, characterizing a comprehensive model of neurophysiological processes behind attentional demand. The analysis of the association between eye and brain-related parameters revealed a statistically significant high correlation (R > 0.7) of eye blink rate with anterofrontal brain activity at 8 Hz, centroparietal brain activity at 12 Hz, and a significant moderate correlation with the participation of right Intra Parietal Sulcus in alpha band (R = -0.62). Due to these findings, this work suggests the possibility of using eye blinks measured from one sensor placed on the forehead as an unobtrusive measure correlating with neural mechanisms underpinning attentional demand.