Search results for "cognition."
showing 10 items of 7004 documents
On the Influence of Affect in EEG-Based Subject Identification
2021
Biometric signals have been extensively used for user identification and authentication due to their inherent characteristics that are unique to each person. The variation exhibited between the brain signals (EEG) of different people makes such signals especially suitable for biometric user identification. However, the characteristics of these signals are also influenced by the user’s current condition, including his/her affective state. In this paper, we analyze the significance of the affect-related component of brain signals within the subject identification context. Consistent results are obtained across three different public datasets, suggesting that the dominant component of the sign…
How women are imagined through conceptual metaphors in United Nations Security Council Resolutions on women, peace and security
2017
United Nations Security Council Resolution 1325 is a landmark pronouncement on the Women, Peace and Security Agenda. Not only does this resolution highlight the important role of the involvement of women in peace processes, but it also stresses the importance of their equal participation in all efforts for the maintenance and promotion of peace. Furthermore, it also triggers the approval of some other resolutions, which are all further elaborations on that first document. The aim of this paper is to analyse, from a cognitive linguistic perspective, the way in which women are actually narrated in these pronouncements by means of the two conceptual metaphors that are most often repeated: WOME…
Corporealising a Healthy Democracy? Inequality, Bodies and Participation
2019
Socio-economic inequality is associated with differentiated levels of health and poor health affects political participation; inequalities are embodied in political life. This contribution, focusin...
Image-Evoked Affect and its Impact on Eeg-Based Biometrics
2019
Electroencephalography (EEG) signals provide a representation of the brain’s activity patterns and have been recently exploited for user identification and authentication due to their uniqueness and their robustness to interception and artificial replication. Nevertheless, such signals are commonly affected by the individual’s emotional state. In this work, we examine the use of images as stimulus for acquiring EEG signals and study whether the use of images that evoke similar emotional responses leads to higher identification accuracy compared to images that evoke different emotional responses. Results show that identification accuracy increases when the system is trained with EEG recordin…
ES1D: A Deep Network for EEG-Based Subject Identification
2017
Security systems are starting to meet new technologies and new machine learning techniques, and a variety of methods to identify individuals from physiological signals have been developed. In this paper, we present ESID, a deep learning approach to identify subjects from electroencephalogram (EEG) signals captured by using a low cost device. The system consists of a Convolutional Neural Network (CNN), which is fed with the power spectral density of different EEG recordings belonging to different individuals. The network is trained for a period of one million iterations, in order to learn features related to local patterns in the spectral domain of the original signal. The performance of the…
What Are the Success Factors of Multilingual Families? Relationships Between Linguistic Attitudes and Community Dynamics
2021
The research focuses on the influence of emotional, cognitive, and social climate on the language choices of multilingual families, and the impact they can have on their general well-being, intergenerational relationships, and the community context. The methodological framework of reference is Grounded Theory. Collected data concern language practices, attitudes, emotions, and generational, trigenerational, and social interactive dynamics of multilingual families. The results include key insights into the variables underlying the linguistic attitudes of multicultural families. Two Network Views suggest that linguistic attitudes, such as the conscious management of specific and complex dynam…
Analysis of Activity States of Local Neuronal Microcircuits in Mouse Brain
2018
Time series of neuronal activity corresponding to different activity states in mouse brain are analyzed in the time domain and the time-frequency domain. The signals are associated with either a slow wave brain state or a persistent brain state. For both states, characteristic spectral features are identified and a simple detector is proposed that is able to identify the brain state with low latency and high accuracy. In practice, being able to monitor the brain state online and in real time is crucial for improved in vivoexperiments and, ultimately, for a causal understanding of brain dynamics.
Engineering of a DNA Polymerase for Direct m6A Sequencing
2017
Methods for the detection of RNA modifications are of fundamental importance for advancing epitranscriptomics. N6-methyladenosine (m6A) is the most abundant RNA modification in mammalian mRNA and is involved in the regulation of gene expression. Current detection techniques are laborious and rely on antibody-based enrichment of m6A-containing RNA prior to sequencing, since m6A modifications are generally "erased" during reverse transcription (RT). To overcome the drawbacks associated with indirect detection, we aimed to generate novel DNA polymerase variants for direct m6A sequencing. Therefore, we developed a screen to evolve an RT-active KlenTaq DNA polymerase variant that sets a mark for…
Mutanome directed cancer immunotherapy
2015
Somatic mutations are important drivers of cancer development. Accumulating evidence suggests that a significant subset of mutations result in neo-epitopes recognized by autologous T cells and thus may constitute the Achilles' heel of tumor cells. T cells directed against mutations have been shown to have a key role in clinical efficacy of potent cancer immunotherapy modalities, such as adoptive transfer of autologous tumor infiltrating lymphocytes and immune checkpoint inhibitors. Whereas these findings strengthen the idea of a prominent role of neo-epitopes in tumor rejection, the systematic therapeutic exploitation of mutations was hampered until recently by the uniqueness of the reperto…
Group analysis of ongoing EEG data based on fast double-coupled nonnegative tensor decomposition
2019
Abstract Background Ongoing EEG data are recorded as mixtures of stimulus-elicited EEG, spontaneous EEG and noises, which require advanced signal processing techniques for separation and analysis. Existing methods cannot simultaneously consider common and individual characteristics among/within subjects when extracting stimulus-elicited brain activities from ongoing EEG elicited by 512-s long modern tango music. New method Aiming to discover the commonly music-elicited brain activities among subjects, we provide a comprehensive framework based on fast double-coupled nonnegative tensor decomposition (FDC-NTD) algorithm. The proposed algorithm with a generalized model is capable of simultaneo…