Who is more prone to distraction? A simple test to evaluate the interference of emotional stimuli in females and males

In order to quantify gender differences in attentional capability depending on the presence of emotional stimuli, the effectiveness of responses to a target stimulus were analysed between groups. Fifty-two men and 52 women carried out two experiments based on the Eriksen flanker task. Half the participants were instructed to indicate the orientation of an arrow without flankers. The other half carried out the same task, but in this case the arrow was flanked by images with sexual or relaxing content. The study suggests that men are faster than women in discriminating the spatial orientation of a relevant stimulus, despite being more prone to distraction by adjacent stimuli. Regarding emotional interference, which is equivalent in both genders, it is higher for images with sexual content compared to those with relaxing content

Stress estimation by the prefrontal cortex asymmetry: Study on fNIRS signals

sure the brain hemodynamic activity in applications to evaluate affective disorders and stress. Using two wavelengths of light, it is possible to monitor relative changes in the concentrations of oxyhemoglobin and deoxyhemoglobin. Besides, the spatial asymmetry in the prefrontal cortex activity has been correlated with the brain response to stressful situations. Methods: We measured prefrontal cortex activity with a NIRS multi-distance device during a baseline period, under stressful conditions (e.g., social stress), and after a recovery phase. We calculated a laterality index for the contaminated brain signal and for the brain signal where we removed the influence of extracerebral hemodynamic activity by using a short channel. Results: There was a significant right lateralization during stress when using the contaminated signals, consistent with previous investigations, but this significant difference disappeared using the corrected signals. Indeed, exploration of the susceptibility to contamination of the different channels showed non-homogeneous spatial patterns, which would hint at detection of stress from extracerebral activity from the forehead. Limitations: There was no recovery phase between the social and the arithmetic stressor, a cumulative effect was not considered. Conclusions: Extracerebral hemodynamic activity provided insights into the pertinence of short channel corrections in fNIRS studies dealing with emotions. It is important to consider this issue in clinical applications including modern monitoring systems based on fNIRS technique to assess emotional states in affective disorders

Spontaneous Breathing Rate Variations Linked to Social Exclusion and Emotion Self-assessment

[EN] The emotional reactions to social exclusion can be associated with physiological responses that could allow researchers to estimate the valence and intensity of the ongoing afective state. In this work, respiratory activity was analysed to verify whether breathing rate variations can be considered as predictive factors of subsequent positive and negative afect after inclusion and exclusion in young women. A standard Cyberball task was implemented and manipulated information was provided to the participants to create both conditions. The participants were socially excluded by limiting their participation to 6% of the total number of passes among three teammates and providing negative feedback about them. The results suggest that breathing rate can be a good option to infer subjective feelings during social interactions and a promising feature to incorporate into modern emotion monitoring systems as an alternative to other physiological measures. Furthermore, the interaction between metaemotion and physiology was studied by recording breathing rate while completing the Positive and Negative Afect Schedule, evidencing a breathing rate increase during the emotion self-assessment only after exclusion.Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLE

Regions of interest computed by SVM wrapped method for Alzheimer’s disease examination from segmented MRI

Accurate identification of the most relevant brain regions linked to Alzheimer’s disease (AD) is crucial in order to improve diagnosis techniques and to better understand this neurodegenerative process. For this purpose, statistical classification is suitable. In this work, a novel method based on support vector machine recursive feature elimination (SVM-RFE) is proposed to be applied on segmented brain MRI for detecting the most discriminant AD regions of interest (ROIs). The analyses are performed both on gray and white matter tissues, achieving up to 100% accuracy after classification and outperforming the results obtained by the standard t-test feature selection. The present method, applied on different subject sets, permits automatically determining high-resolution areas surrounding the hippocampal area without needing to divide the brain images according to any common template.This work was partly supported by the MICINN under the TEC2012-34306 project and the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía, Spain) under the Excellence Projects P09-TIC-4530 and P11-TIC-7103. Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI; National Institutes of Health Grant U01 AG024904).This research was also supported by NIH grants P30 AG010129, K01 AG030514, and the Dana Foundation

Affective Valence Detection from EEG Signals Using Wrapper Methods

In this work, a novel valence recognition system applied to EEG signals is presented. It consists of a feature extraction block followed by a wrapper classification algorithm. The proposed feature extraction method is based on measures of relative energies computed in short‐time intervals and certain frequency bands of EEG signal segments time‐locked to the stimuli presentation. These measures represent event‐related desynchronization/synchronization of underlying brain neural networks. The subsequent feature selection and classification steps comprise a wrapper technique based on two different classification approaches: an ensemble classifier, i.e., a random forest of classification trees and a support vector machine algorithm. Applying a proper importance measure from the classifiers, the feature elimination has been used to identify the most relevant features of the decision making both for intrasubject and intersubject settings, using single trial signals and ensemble averaged signals, respectively. The proposed methodologies allowed us to identify a frontal region and a beta band as the most relevant characteristics, extracted from the electrical brain activity, in order to determine the affective valence elicited by visual stimuli

Flight simulator and fNIRS : study of relation between acute stress and cognitive workload

In aviation, knowing the internal state of pilots is desirable to prevent and detect abnormal situations such as an excessive cognitive workload (CW) or acute stress, both known to impact human performance 1. Detecting these states becomes crucial with the possible emergence of Single Pilot Operations (SPO), during which tasks will be largely supported by a single pilot and the aircraft systems. The mental constructs of CW and acute stress have been extensively studied in the human factor literature, but the analysis of their respective impact in the same ecological situations remains poorly studied. In the current study, twenty-one private pilots from the French Civil Aviation University were recruited. They all performed two realistic flight simulator scenarios with the same difficult level and duration (around 35 minutes each). The CW was manipulated with the difficulty of a secondary task (low CW vs high CW; for details, see [2]) and the level of stress was manipulated by means of a social stressor (low arousal vs high arousal). We examined brain hemodynamic activity via functional near infrared spectroscopy (fNIRS) with a portable NIRS system (NIRSport, NIRx Medical Technologies, NY, USA)

Cardiovascular Activity linked to the Emotional State and Cognitive Workload during a Flight Simulation

The identification of physiological markers of emotional and cognitive fluctuations during a flight can be useful to alert of risky situations due to their possible impact on pilot’s mental state and performance. In this study, heart rate (HR) and other features, such as R-R peak interval variability and the spectral power of specific frequency bands, have been extracted from ECG recordings throughout flight simulations. The temporal variation of these features within different experimental conditions has been explored to verify their reliability to discriminate episodes of mental overload. Our results show that the monotonic decrease of HR reflects the emotional regulation, mainly under secondary low cognitive overload. Conversely, the increase of the root mean square successive differences was linked to higher cognitive workload situations. Furthermore, the habituation analysis reveals that these features are severely affected when an external cognitive deman

Respiration and Heart Rate Modulation Due to Competing Cognitive Tasks While Driving

Research works on operator monitoring underline the benefit of taking into consideration several signal modalities to improve accuracy for an objective mental state diagnosis. Heart rate (HR) is one of the most utilized systemic measures to assess cognitive workload (CW), whereas, respiration parameters are hardly utilized. This study aims at verifying the contribution of analyzing respiratory signals to extract features to evaluate driver’s activity and CW variations in driving. Eighteen subjects participated in the study. The participants carried out two different cognitive tasks requiring different CW demands, a single task as well as a competing cognitive task realized while driving in a simulator. Our results confirm that both HR and breathing rate (BR) increase in driving and are sensitive to CW. However, HR and BR are differently modulated by the CW variations in driving. Specifically, HR is affected by both driving activity and CW, whereas, BR is suitable to evidence a variation of CW only when driving is not required. On the other hand, spectral features characterizing respiratory signal could be also used similarly to HR variability indices to detect high CW episodes. These results hint the use of respiration as an alternative to HR to monitor the driver mental state in autonomic vehicles in order to predict the available cognitive resources if the user has to take over the vehicle

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac