Nebrija Universidad
  • Madrid, Spain
Recent publications
The study of consciousness is considered by many one of the most difficult contemporary scientific endeavors and confronts several methodological and theoretical challenges. A central issue that makes the study of consciousness so challenging is that, while the rest of science is concerned with problems that can be verified from a "third person" view (i.e., objectively), the study of consciousness deals with the phenomenon of subjective experience, only accessible from a "first person" view. In the present article, we review early (starting during the late 19th century) and later efforts on measuring consciousness and its absence, fo-cusing on the two main approaches used by researchers within the field: objective (i.e., performance based) and subjective (i.e., report based) measures of awareness. In addition, we compare the advantages and disadvantages of both types of awareness measures, evaluate them according to different methodological considerations, and discuss, among other issues, the possibility of comparing them by transforming them to a common sensitivity measure (d′). Finally, we explore several new approaches-such as Bayesian models to support the absence of awareness or new machine-learning based decoding models-as well as future challenges-such as measuring the qualia, the qualitative contents of awareness-in consciousness research.
The identification of visually presented words tolerates distortions in the input format, as Hannagan et al. Plos One, 7, e32121, (2012) demonstrated in a masked priming lexical decision task, showing sizable identity-priming effects with CAPTCHA-like primes. This tolerance to distortion has two potential explanations: bottom-up normalization in the encoding stage (Dehaene et al., Trends in Cognitive Sciences, 9, 335–341, 2005) or top-down lexical feedback (McClelland & Rumelhart, Psychological Review , 88 , 375–407, 1981). To disentangle the predictions of these accounts, we conducted two masked identity-priming experiments with printed and CAPTCHA-like distorted primes on high- and low-frequency words. The rationale was that, in the distorted format, high-frequency words would benefit more from top-down feedback than low-frequency words. Results in the lexical decision experiment showed that, for high-frequency words, identity-priming effects were only slightly greater for printed than for CAPTCHA-like primes, whereas this difference was larger for low-frequency words. In contrast, when employing the same-different matching task, which does not require lexical access, the identity-priming effect was greater for printed primes and was unaffected by word frequency. Thus, during lexical access, top-down feedback may help normalize the visual input in the early stages of word recognition, challenging bottom-up models of visual word recognition.
Introduction Reading is a fundamental cognitive activity that is influenced by both textual and external environmental factors, although the latter has been less thoroughly explored. This study aims to examine the impact of environmental visual conditions on reading performance using Virtual Reality (VR) technology. Methods We conducted two experiments to assess the effects of visual contrast and simulated weather conditions on reading dynamics. In Experiment 1, we measured single-word recognition speed using a lexical decision task under different visual contrasts and weather conditions. In Experiment 2, we assessed reading dynamics during a sentence reading task, analyzing how visual contrast and simulated sunny versus rainy weather conditions affected reading behavior, particularly focusing on reading speed and eye fixations. Results In Experiment 1, high visual contrast, particularly under sunny conditions, significantly enhanced single-word recognition speed, indicating a notable influence of environmental visual conditions. In Experiment 2, visual contrast had minimal effect on sentence reading; however, sunny weather facilitated faster reading times, while rainy scenarios increased the number of eye fixations. Discussion These findings suggest that environmental factors, such as weather conditions, can significantly affect reading behavior. The study contributes to the understanding of key environmental influences on reading in everyday life contexts and has implications for the ergonomic design of reading materials, especially for outdoor settings and VR environments. Additionally, the integration of controlled stimuli within VR increases the ecological validity of reading research, underscoring the potential of VR as a powerful tool for cognitive research.
This article aims to elucidate the influence of the Chinese elite’s geographic perception on shaping geopolitical codes and its impact on the foreign policy of the People’s Republic of China (PRC). For this purpose, the study focuses on the role of internal and external geopolitical factors in the configuration of Chinese leaders’ spatial vision. Internal geopolitical factors encompass China’s involvement in the global economy, its geographic characteristics, and the geographic distribution of its population. External geopolitical factors include the regional and global distribution of power and China’s territorial disputes with neighboring countries. Regarding methodology, the study draws on a wide range of sources, including geographic and economic statistical data, Chinese leaders’ public statements, PRC’s decision-making bodies documents, and academic studies and reports. The primary findings suggest that geopolitical factors have constrained the strategic choices available to the Chinese elite and favored a seaward-oriented foreign policy, which have been reflected in China’s geopolitical codes. In this context, the China Seas, and to a lesser extent the Indian Ocean, assume pivotal roles in the PRC’s efforts to project power and expand its influence.
Background: The main objectives of this study were to analyze the effect of early specialization in swimming and to observe the general patterns of success of two different sport specialization models [Spanish (SPA) and United States of American (USA) swimmers] participating in World Championships (WCs) and Olympic Games (OGs) between the years 2006 and 2021 of all swimming strokes and distances. Methods: Descriptive analyses and contingency tables were examined for all the variables. Explanatory models of the z scores were estimated from age depending on the events’ distances and strokes. Quadratic regression models were developed to capture the behavior of the variable time with parabolic functions, and the significance of the global model and the predictor variables (age) were also evaluated. In addition, the optimal age (peak performance) as well as the curvature of the model were analyzed. These models were compared between SPA and USA swimmers. Results: The results showed that the main differences in the patterns to success between SPA and USA were the earlier participation of USA swimmers in high-level competitions, as well as the greater number of participants for all the strokes, events, genders, and competitions. Age peak performance in short distances was lower for Spanish swimmers, obtaining the opposite situation for long distances. Conclusions: Being a finalist in junior WCs did not influence success in the finals of the senior WCs and OGs. Main differences in general patterns of success between SPA and USA showed younger swimmers participating in short-distance events, backstroke, and butterfly for USA swimmers and older swimmers taking part in butterfly and short-distance events for SPA.
We investigated the dose-response relationship between aircraft noise levels and noise annoyance in the French DEBATS study including 1244 participants in 2013 and a sub-study of the German NORAH study including 1039 participants in 2014. In both studies, annoyance due to aircraft noise was assessed using the ICBEN 5-points question. High annoyance was defined according to ISO/TS-15666 (HAV). Outdoor aircraft noise levels were modelled for the participants' home addresses. The moderation roles of noise sensitivity, gender and age were investigated. About 18% of the participants in the DEBATS study reported to be highly annoyed vs 54% in the NORAH study. The mean noise levels (Lden) were similar (54 dBA in DEBATS and 52 dBA in NORAH). In the pooled analysis, high noise annoyance was associated not only with aircraft noise levels, but also with non-acoustical factors such as noise sensitivity, age and trust in authorities. Noise sensitivity moderates the effect of aircraft noise levels on aircraft noise annoyance (p-value of interaction = 0.02), while age and gender do not.
Radar-based Human Activity Recognition (HAR) is popular because of its privacy and contactless sensing capabilities. However, a major challenge in this area is the lack of large and diverse datasets. In response, we present a novel framework that uses generative models to transform textual descriptions into motion data, thereby simulating radar signals. This approach significantly enriches the realism and diversity of the dataset, especially for infrequent but critical activities such as falls and abnormal walking. Textual descriptions capture the semantic complexity of human actions, thereby improving intra-class diversity. Our framework scales the data generation process by using a lightweight physics-based simulator and improves diversity by controlling gait variation, multi-viewpoint adaptation and background noise modelling. The experiments show that data diversity is a critical factor for fair model comparisons, and that the simulated data can effectively improve performance through sim-to-real transfer learning.
In the following section, an example of the methodological approach for assessing the carbon footprint of an UPMP is developed, through the basis of the Community of Madrid. A set of features and municipalities as locations with different features has been selected with a view to limiting the scope, and the carbon footprint has been calculated for the urban planning major land uses: residential and tertiary.
The tool for calculating greenhouse gas emissions generated by urban planning is developed in an Excel workbook consisting of 11 main tabs.
There is no agreed proposal on how to build a tool that allows to evaluate the relationship between urban planning and sustainability in the city, in terms of energy supply and calculation of greenhouse gas (GHG) emissions and consequently the impact on climate change.
This study examines when the vocabulary knowledge of Japanese heritage speakers (HSs; N = 427, M age = 9.96, female = 213) begins to diverge from monolingual counterparts ( N = 136, M age = 6.69, female = 65) and what factors explain individual differences in HS development. Vocabulary of HSs began to diverge from 5.61 years and this difference lasted until they were young adults. We also administered a fit‐for‐purpose questionnaire in 2021–2023 and identified six experiential latent factors: Holiday, School, Community, Proficiency, Literacy, and Home. Structural modeling indicates that Holiday predicted vocabulary scores, while Holiday and Literacy predicted Proficiency. Our findings highlight the importance of immersion experiences and literacy engagement for heritage language development.
Casasanto (Journal of Experimental Psychology: General, 138, 351-367, 2009) conceptualised the body-specificity hypothesis by empirically finding that right-handed people tend to associate a positive valence with the right side and a negative valence with the left side, whilst left-handed people tend to associate a positive valence with the left side and negative valence with the right side. Thus, this was the first paper that showed a body-specific space-valence mapping. These highly influential findings led to a substantial body of research and follow-up studies, which could confirm the original findings on a conceptual level. However, direct replications of the original study are scarce. Against this backdrop and given the replication crisis in psychology, we conducted a direct replication of Casasanto's original study with 2,222 participants from 12 countries to examine the aforementioned effects in general and also in a cross-cultural comparison. Our results support Casasanto's findings that right-handed people associate the right side with positivity and the left side with negativity and vice versa for left-handers.
Two views contend to account for the processes at play during the early stages of visual word recognition. The first holds that these stages are not modulated by the idiosyncratic properties of different languages. The second maintains that the structural properties of the language determine the weighting of the different domains of linguistic knowledge (e.g., orthographic and morphological domains may be differentially weighted across languages). To explore this question, we focused on orthographic priming in Arabic. In this Semitic language, lexical representations are claimed to be based on morphological similarity, with little or no role for orthographic similarity. We conducted two masked priming experiments using the yes–no and go/no-go versions of the lexical decision task to determine if Arabic target words (e.g., مدير ‘mudyr’, director) are facilitated by nonword primes that are orthographically but not morphologically related (i.e., pairs share neither a root nor a word pattern; e.g.,ماير ‘maAyr’) relative to unrelated primes. Results showed faster responses for the orthographically related target words than for the unrelated target words in the two experiments. These findings favor the view that the early phases of visual word processing in Semitic and Indo-European languages are fundamentally the same.
Research on the interplay between language and emotion has shown evidence that the affective content of words influences their recognition. However, the direction of the effects is not clear, as there are mixed findings regarding the role of positive and, especially, negative valence. We conducted a Bayesian multi-level meta-analysis to examine the role of valence in visual word recognition, focusing on the lexical decision task. The results revealed a facilitative effect of positive valence on lexical decision times. That is, positive words led to faster responses than both negative and neutral words. In contrast, negative valence did not have any effect, although the analysis of several moderator variables suggested that there might be a facilitative effect in some cases, specifically, when negative words elicit very strong and intense emotions. These results shed light on the complexities of emotional word processing. They also point to the need for psycholinguistic models to take affective information into account, and thus provide a complete view of visual word recognition.
The objective of this review is to provide a comprehensive examination of the role of microbial metabolites in the progression of neurodegenerative diseases, as well as to investigate potential therapeutic interventions targeting the microbiota. A comprehensive literature search was conducted across the following databases: PubMed, Scopus, Web of Science, ScienceDirect, and Wiley. Key terms related to the gut microbiota, microbial metabolites, neurodegenerative diseases, and specific metabolic products were used. The review included both preclinical and clinical research articles published between 2000 and 2024. Short-chain fatty acids have been demonstrated to play a crucial role in modulating neuroinflammation, preserving the integrity of the blood–brain barrier, and influencing neuronal plasticity and protection. Furthermore, amino acids and their derivatives have been demonstrated to exert a significant influence on CNS function. These microbial metabolites impact CNS health by regulating intestinal permeability, modulating immune responses, and directly influencing neuroinflammation and oxidative stress, which are integral to neurodegenerative diseases. Therapeutic strategies, including prebiotics, probiotics, dietary modifications, and fecal microbiota transplantation have confirmed the potential to restore microbial balance and enhance the production of neuroprotective metabolites. Furthermore, novel drug developments based on microbial metabolites present promising therapeutic avenues. The gut microbiota and its metabolites represent a promising field of research with the potential to advance our understanding of and develop treatments for neurodegenerative diseases.
This article presents research conducted within the School of Computational Thinking and Artificial Intelligence (EPCIA in its original form in Spanish) project, an initiative developed by the Spanish Ministry of Education and Vocational Training during the 2020-21 academic year. The study investigated whether it is possible to contribute to the development of students’ computational thinking skills and artificial intelligence (AI) literacy through programming activities using the Scratch language and the Machine Learning for Kids platform. The study involved 133 teachers and more than 2,000 students, from 4th to 8th grade, with representation from 17 of the 19 Spanish regions. Students took a quantitative test on computational thinking and another on AI before and after the intervention, and teachers and students also took a questionnaire at the end of it. The results showed that: i) quantitative tests can be used to reliably measure, in terms of internal consistency, the level of development of computational thinking and AI literacy in the Spanish school population of these ages; ii) it is possible to develop students’ computational thinking skills and raise their level of AI literacy through programming activities; iii) the intervention contributed to demystifying the main prejudices regarding AI; iv) a gender gap was found in relation to previous knowledge and experiences with these topics. Overall, the study concluded that introducing the foundations of AI in primary and secondary education in Spain is appropriate, feasible, and relevant.
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Alice Foucart
  • Centro de Investigación Nebrija en Cognición - Facultad de Lenguas y Educación
Alicia Coduras
  • Entrepreneurship Chair, Health Research
M. Pilar Vélez
  • Engineering School
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