Are Females More Responsive to Emotional Stimuli? A Neurophysiological Study Across Arousal and Valence Dimensions

Men and women seem to process emotions and react to them differently. Yet, few neurophysiological studies have systematically investigated gender differences in emotional processing. Here, we studied gender differences using Event Related Potentials (ERPs) and Skin Conductance Responses (SCR) recorded from participants who passively viewed emotional pictures selected from the International Affective Picture System (IAPS). The arousal and valence dimension of the stimuli were manipulated orthogonally. The peak amplitude and peak latency of ERP components and SCR were analyzed separately, and the scalp topographies of significant ERP differences were documented. Females responded with enhanced negative components (N100 and N200), in comparison to males, especially to the unpleasant visual stimuli, whereas both genders responded faster to high arousing or unpleasant stimuli. Scalp topographies revealed more pronounced gender differences on central and left hemisphere areas. Our results suggest a difference in the way emotional stimuli are processed by genders: unpleasant and high arousing stimuli evoke greater ERP amplitudes in women relatively to men. It also seems that unpleasant or high arousing stimuli are temporally prioritized during visual processing by both genders

A review of physical and cognitive interventions in aging

Maintaining a healthy brain is a critical factor for the quality of life of elderly individuals and the preservation of their independence. Challenging aging brains through cognitive training and physical exercises has shown to be effective against age-related cognitive decline and disease. But how effective are such training interventions? What is the optimal combination/strategy? Is there enough evidence from neuropsychological observations, animal studies, as well as, structural and functional neuroimaging investigations to interpret the underlying neurobiological mechanisms responsible for the observed neuroplasticity of the aging brain? This piece of work summarizes recent findings toward these questions, but also highlights the role of functional brain connectivity work, an emerging discipline for future research in healthy aging and the study of the underlying mechanisms across the life span. The ultimate aim is to conclude on recommended multimodal training, in light of contemporary trends in the design of exergaming interventions. The latter issue is discussed in conjunction with building up neuroscientific knowledge and envisaged future research challenges in mapping, understanding and training the aging brain

A review of physical and cognitive interventions in aging

Maintaining a healthy brain is a critical factor for the quality of life of elderly individuals and the preservation of their independence. Challenging aging brains through cognitive training and physical exercises has shown to be effective against age-related cognitive decline and disease. But how effective are such training interventions? What is the optimal combination/strategy? Is there enough evidence from neuropsychological observations, animal studies, as well as, structural and functional neuroimaging investigations to interpret the underlying neurobiological mechanisms responsible for the observed neuroplasticity of the aging brain? This piece of work summarizes recent findings toward these questions, but also highlights the role of functional brain connectivity work, an emerging discipline for future research in healthy aging and the study of the underlying mechanisms across the life span. The ultimate aim is to conclude on recommended multimodal training, in light of contemporary trends in the design of exergaming interventions. The latter issue is discussed in conjunction with building up neuroscientific knowledge and envisaged future research challenges in mapping, understanding and training the aging brain. © 2014 Elsevier Ltd

On the classification of emotional biosignals evoked while viewing affective pictures: An integrated data-mining-based approach for healthcare applications

Recent neuroscience findings demonstrate the fundamental role of emotion in the maintenance of physical and mental health. In the present study, a novel architecture is proposed for the robust discrimination of emotional physiological signals evoked upon viewing pictures selected from the International Affective Picture System (IAPS). Biosignals are multichannel recordings from both the central and the autonomic nervous systems. Following the bidirectional emotion theory model, IAPS pictures are rated along two dimensions, namely, their valence and arousal. Following this model, biosignals in this paper are initially differentiated according to their valence dimension by means of a data mining approach, which is the C4.5 decision tree algorithm. Then, the valence and the gender information serve as an input to a Mahalanobis distance classifier, which dissects the data into high and low arousing. Results are described in Extensible Markup Language (XML) format, thereby accounting for platform independency, easy interconnectivity, and information exchange. The average recognition (success) rate was 77.68% for the discrimination of four emotional states, differing both in their arousal and valence dimension. It is, therefore, envisaged that the proposed approach holds promise for the efficient discrimination of negative and positive emotions, and it is hereby discussed how future developments may be steered to serve for affective healthcare applications, such as the monitoring of the elderly or chronically ill people

Detecting neurophysiological alterations during Mild Cognitive Impairment and Dementia using wavelet-based energy computation and a Mahalanobis Distance classifier

Recently, a transitional stage, called Mild Cognitive Impairment (MCI) has been identified. Early MCI detection is of crucial importance for preventing dementia onset. The aim of this study is to provide a classification framework able to discriminate subtle alterations due to neurodegenerative processes. Primary attention was given at the MCI stage. Therefore two MCI groups were formed according the patient's performance in the Montreal Cognitive Assessment (MoCA) test; a group of 39 patient with a low cognitive decline (MCI-1; MoCA ≥ 25), and a group of 31 patients with moderate cognitive decline group (MCI-2; MoCA < 25). In addition, we tested 17 healthy control participants, and 14 mild demented patients. Participants underwent a full neuropsychologic examination. Application of the Independent Component Analysis (ICA) and visual inspection of EEG data during resting state condition with eyes closed was initially adopted for noise rejection. Then, the energy for each frequency band was computed through discrete wavelet transform (DWT). These spectral components for 57 electrodes served as an input to a classification system employing Mahalanobis Distance. Classification results (84.16% overall accuracy) demonstrated the system's robustness and reliability. Discrimination reached 82.35% for healthy controls, 92.31% for MCI-1, 74.19% for MCI-2 and 85.71% for mild demented patients. The classification system is proposed in order to supplement the neuropsychologic examination and to correlate subtle cognitive deficits revealed by MoCA with modified neurophysiological patterns, providing thus a better understanding to the progression of neurodegenerative mechanisms

Systemic redox biomarkers suggest non-redox mediated processes in the prevention of bed rest-induced muscle atrophy after exercise training: The Cologne RSL study

It has been previously reported that eccentric-biased exercise training prevents the decreases in lean body mass after 60 days of head tilt down bed rest (“Cologne RSL Study”). The aim of the present study, as a part of Cologne RSL Study, was to investigate whether these anti-atrophy effects of exercise training are regulated by redox processes, as assessed indirectly via redox biomarkers in blood and urine. Twenty-four volunteers (N = 24) participated in a randomized controlled study and were randomly divided into two groups: a jump training group (JUMP, n = 12) that performed a specific eccentric-biased training protocol on a Sledge Jump System and a control group (CON, n = 11; one drop-out) that did not perform any exercise. All participants maintained a 6° head tilt down position for 24 h/day for 60 days. Redox measurements in plasma, erythrocytes and urine were performed at several time points throughout the study (i.e., baseline, intervention and recovery phases). A main effect of time was found for all dependent variables (P &amp;lt; .05). In particular, plasma protein carbonyls, erythrocyte catalase activity and urine F2-isoprostanes increased, while erythrocyte glutathione concentration decreased over time in both groups. In contrast, neither a main effect of group nor a significant group × time interaction was found in any of the measured variables (P &amp;gt; .05). In conclusion, our findings in systemic redox biomarkers indicate that the anti-atrophy effects of exercise training during a 60-day bed rest protocol are not regulated by redox processes. © 2019 IA

Neuroscientific tools in the cockpit: towards a meaningful decision support system for fatigue risk management

Fatigued pilots are prone to experience cognitive disorders that degrade their performance and adherence to high safety standards. In light of the current challenging context in aviation, we report the early phase of our ongoing project on the re-evaluation of human factors research for flight crew. Our motivation stems from the need for aviation organisations to develop decision support systems for operational aviation settings, able to feed-in in the organisations’ fatigue risk management efforts. Key criteria to this end are the need for the least possible intrusiveness and the added information value for a safety system. Departing from the problems in compliance-focused fatigue risk management and the intrusive nature of clinical studies, we report a neuroscientific methodology able to yield markers that can be easily integrated in a decision support system at the operational level. Reporting the preliminary phase of our live project, we evaluate the tools suitable for the development of a system that tracks subtle pilot states, such as drowsiness and micro-sleep episodes