“Some like it hot”:spectators who score high on the personality trait openness enjoy the excitement of hearing dancers breathing without music

Music is an integral part of dance. Over the last 10 years, however, dance stimuli (without music) have been repeatedly used to study action observation processes, increasing our understanding of the influence of observer’s physical abilities on action perception. Moreover, beyond trained skills and empathy traits, very little has been investigated on how other observer or spectators’ properties modulate action observation and action preference. Since strong correlations have been shown between music and personality traits, here we aim to investigate how personality traits shape the appreciation of dance when this is presented with three different music/sounds. Therefore, we investigated the relationship between personality traits and the subjective esthetic experience of 52 spectators watching a 24 min lasting contemporary dance performance projected on a big screen containing three movement phrases performed to three different sound scores: classical music (i.e., Bach), an electronic sound-score, and a section without music but where the breathing of the performers was audible. We found that first, spectators rated the experience of watching dance without music significantly different from with music. Second, we found that the higher spectators scored on the Big Five personality factor openness, the more they liked the no-music section. Third, spectators’ physical experience with dance was not linked to their appreciation but was significantly related to high average extravert scores. For the first time, we showed that spectators’ reported entrainment to watching dance movements without music is strongly related to their personality and thus may need to be considered when using dance as a means to investigate action observation processes and esthetic preferences

Neuroarchitecture of musical emotions

La respuesta emocional ante la música, o emoción musical, es una respuesta universal que depende de diferentes procesos psicológicos y recluta una extensa red de estructuras neuronales. Mediante el empleo de técnicas como la electroencefalografía, la resonancia magnética funcional y los estudios con población clínica e individuos con formación musical previa, se ha empezado a dilucidar estos mecanismos cerebrales. El objetivo de este artículo es hacer una revisión de los trabajos más relevantes en los que se identifican los correlatos neuronales de la emoción musical, desde los procesos más automáticos hasta los más complejos, y comprender cómo interaccionan en el cerebro. En concreto, se describe cómo la presentación de música emocional está asociada a una respuesta rápida en estructuras talámicas y subtalámicas, acompañada por cambios electrodérmicos y endocrinos. También se explica que el procesamiento de la emoción musical implica la activación de la corteza auditiva y estructuras límbicas y paralímbicas, como la amígdala, la corteza cingulada anterior o el hipocampo, lo que demuestra la contribución del sistema límbico a la emoción musical. Asimismo, se detalla cómo la emoción musical depende de los significados semántico y sintáctico de la música, procesados en áreas temporales y parietofrontales, respectivamente. Además, se mencionan trabajos recientes que han demostrado cómo los mecanismos de simulación emocional también contribuyen a la emoción musical. Por último, se hace un resumen de estos trabajos, comentando sus limitaciones y ofreciendo alternativas para seguir avanzando en el estudio de la neuroarquitectura de la emoción musical

Aesthetic image statistics vary with artistic genre

Research to date has not found strong evidence for a universal link between any single low-level image statistic, such as fractal dimension or Fourier spectral slope, and aesthetic ratings of images in general. This study assessed whether different image statistics are important for artistic images containing different subjects and used partial least squares regression (PLSR) to identify the statistics that correlated most reliably with ratings. Fourier spectral slope, fractal dimension and Shannon entropy were estimated separately for paintings containing landscapes, people, still life, portraits, nudes, animals, buildings and abstracts. Separate analyses were performed on the luminance and colour information in the images. PLSR fits showed shared variance of up to 75% between image statistics and aesthetic ratings. The most important statistics and image planes varied across genres. Variation in statistics may reflect characteristic properties of the different neural sub-systems that process different types of image

Dance as a Subject for Empirical Aesthetics

The purpose of this paper is to highlight the possibilities that research on dance appreciation offers empirical aesthetics, as well as the challenges it poses. Behavioral and neuroimaging approaches have, to date, mainly focused on the perception and recognition of human body movement and structure. A small number of studies, nonetheless, have explicitly taken the basic research on the perceptual, emotional and cognitive processes engaged during movement observation, together with their neural concomitants, as a starting point to understand the aesthetic experience triggered by the observation of a dance. We provide an overview of these studies and, thereafter, point out avenues for future research on dance appreciation within the scope of empirical aesthetics. We also note some methodological and conceptual issues that should be taken into account in the design of empirical studies of the aesthetic appreciation of dance, including dance theory scholarship and humanistic approaches to dance practice. Finally, we describe how common movement features of dance styles around the world suggest that humans may be endowed with an evolved cognitive ability to appreciate and to be aesthetically moved by dance

Domed buildings in the twelfth century. The monastery of "Santa Maria de Moreruela"

The monastery of “Santa Maria de Moreruela”, whose origins according to many historians date from the twelfth century, is the first of the Cistercian enclaves built on the Iberian Peninsula. It is now in ruins and is considered one of the great examples of the cultural heritage of the province of Zamora. This paper aims to raise awareness of how the Cistercian churches were designed, the contribution of the Castilian quarries to their construction, and the development of the vaults over the time passed from their inception until the completion of the work, using this Monastery as an example. European culture came to Castile with the appearance of the Romanesque style from the hands of the French Benedictine monks; later, Cistercian monks introduced the Gothic style. Thus, the vaults have evolved from the Romanesque rounded vault to the Gothic ogive, the changes being attributed to structural elements and also to the design of thinner walls with more lights. In the case of the Monastery of Moreruela, this has a basilica church plan, which is typical of the twelfth century, with the same design as that built by the Cistercian order in the French Midi, who along the years of construction changed the design of their arches and vaults. The most significant vaults of the church of the Monastery of Moreruela, whose styles changed as they were built during several phase,, are classified and displayed in the order in their construction: Header.Transept. Central nave. Aisle

Modulation of motor cortex activity in a visual working memory task of hand images

Recent studies suggest that brain regions engaged in perception are also recruited during the consolidation interval of the percept in working memory (WM). Evidence for this comes from studies showing that maintaining arbitrary visual, auditory, and tactile stimuli in WM elicits recruitment of the corresponding sensory cortices. Here we investigate if encoding and WM maintenance of visually perceived body-related stimuli engage just visual regions, or additional sensorimotor regions that are classically associated with embodiment processes in studies of body and action perception. We developed a novel WM paradigm in which participants were asked to remember body and control non-body-related images. In half of the trials, visual-evoked activity that was time-locked to the sight of the stimuli allowed us to examine visual processing of the stimuli to-be-remembered (visual-only trials). In the other half of the trials we additionally elicited a task irrelevant key pressing during the consolidation interval of the stimuli in WM. This manipulation elicited motor-cortical potentials (MCPs) concomitant to visual processing (visual-motor trials). This design allowed us to dissociate motor activity depicted in the MCPs from concurrent visual processing by subtracting activity from the visual-only trials to the compound activity found in the visual-motor trials. After dissociating the MCPs from concomitant visual activity, the results show that only the body-related images elicited neural recruitment of sensorimotor regions over and above visual effects. Importantly, the number of body stimuli to-be-remembered (memory load) modulated this later motor cortical activity. The current observations link together research in embodiment and WM by suggesting that neural recruitment is driven by the nature of the information embedded in the percept

Análisis de electroencefalogramas para la detección automática de las fases del sueño

Las enfermedades del sueño son cada vez más comunes debido al estresante estilo de vida de la sociedad actual. Un paso fundamental en su estudio y diagnóstico es detectar correctamente las diferentes fases del sueño. Avances en áreas como el Deep learning han permitido desarrollar métodos que automatizan esta detección, presentando una alternativa a la clasificación mediante inspección visual realizada hasta la fecha. En este trabajo se ha indagado en el uso de redes neuronales convolucionales (CNN) como clasificadores de fases del sueño, usando para ello la señal de electroencefalograma (EEG). El comportamiento de esta señal difiere entre niños y adultos. Sin embargo, los estudios publicados hasta ahora se han centrado únicamente en pacientes adultos, lo que provoca que los modelos de clasificación no sean fácilmente generalizables. Conseguir un método de clasificación basado en CNN que permita una detección precisa de las fases del sueño en niños, y comprobar si se puede entrenar un modelo que alcance resultados óptimos al evaluar sujetos de diferentes edades, son los objetivos principales de este trabajo. Para ello, se han usado dos amplias bases de datos públicas procedentes de los estudios Sleep Heart Health Study (SHHS) y Childhood Adenotonsillectomy Trial (CHAT), que contienen 5793 registros de adultos y 453 registros de niños, respectivamente. El proceso de entrenamiento y optimización de la red CNN se ha probado modificando el número de capas y su parámetro de regularización, este último buscando asegurar que no haya sobreentrenamiento. Tras conseguir un modelo con alto rendimiento al clasificar la población adulta, se ha evaluado dicho modelo en los registros pediátricos. El mismo procedimiento se ha realizado de manera inversa, probando en la población adulta un modelo entrenado únicamente con niños. Además, se ha obtenido un modelo conjunto usando registros de ambas bases de datos en los grupos de entrenamiento/validación/test. Para homogeneizar las señales de las dos bases, se ha implementado re-muestreo a la misma frecuencia, re-referenciado a la media de los canales utilizados en cada caso, y estandarización para igualar los límites de amplitud. Los resultados muestran que los modelos entrenados con registros de una única base de datos clasifican con alta precisión siempre que se apliquen sobre sujetos en los mismos rangos de edad, consiguiéndose una precisión del 0.815 y un kappa de Cohen de 0.738 en el caso de sujetos adultos y precisión de 0.84 y kappa de 0.77 en el caso de niños, lo que es coherente con estudios previos. No obstante, al clasificar un grupo de edad diferente, estos valores disminuyen. Sin embargo, el modelo entrenado con registros de diferentes edades sí que consigue detectar de manera precisa registros de ambas bases, llegando a una precisión de 0.81 y a un kappa de 0.75 al evaluarlo en un grupo de test conjunto. Estos resultados sugieren la necesidad de incluir sujetos de diferentes edades en el entrenamiento para conseguir modelos más generalizables.Sleep disorders are very common nowadays due to the stressful lifestyle of the current society. A fundamental step in the study and diagnosis of these disorders is to successfully detect the different sleep stages. Recent investigation in fields like Deep learning has led to the development of methods that automatize this detection, becoming an alternative to the visual classification mostly used up to the date. This project explores the application of convolutional neural networks (CNN) as methods for sleep staging classification, using the brain signal of the electroencephalogram (EEG). The behavior of this signal changes between children and adults. However, studies published up to the date mostly focus on grown up patients, issue that causes a poor generalization of the classification models when applied to other age ranges. Finding a classification method based on CNN that shows an accurate detection of children´s sleep stages, and training a model that reaches high performance when evaluated with subjects of different ages, are the two main goals of this work. In order to achieve these goals, two large public data bases have been used, coming from the Sleep Heart Health Study (SHHS) and the Childhood Adenotonsillectomy Trial (CHAT), and containing 5793 adults´ recordings and 453 children´s recordings, respectively. The process of training and optimizing the neural network has been conducted by varying the number of convolutional layers and the dropout percentage, the latter being used to minimize the risk of model overfitting. Once an effective model for the classification of adults´ recordings is found, it gets tested with the pediatric recordings. The same procedure is followed the other way around, testing with the recordings of adults a model trained only using kids´ signals. Furthermore, a mixed model is obtained by including subjects from both data bases in the training/validation/test groups. With the aim of homogenize the signals of the two data bases, three different actions have been taken: re-sampling the recordings to the same frequency, applying an average reference, and standardizing the signals to keep them with in the same amplitude limits. The results show that the models trained with just one of the data bases only classify accurately recordings from subjects of that data base, obtaining a Kappa coefficient of 0.74 and an accuracy of 0.82 when just using grown up subjects and a Kappa of 0.77 and accuracy of 0.84 with only children. However, when testing these models on subjects of different age from the ones in the training set the level of performance decreased significantly. On the contrary, the mixed model does succeed when classifying recordings from both age ranges, obtaining an accuracy of 0.81 and a Kappa of 0.75 in the classification of a test group formed by the same number of adults and children. These results support the need to consider subjects of different ages when developing methods for the automatic detection of sleep stages, so the models obtained can adapt to a wider range of patients.Grado en Ingeniería de Tecnologías de Telecomunicació

Influence of Zn excess on compositional, structural and vibrational properties of Cu2ZnSn0.5Ge0.5Se4 thin films and their effect on solar cell efficiency

This Accepted Manuscript will be available for reuse under a CC BY-NC-ND licence after 24 months of embargo periodThe effect of Zn content on compositional, structural and vibrational properties of Cu2ZnSn1-xGexSe4 (CZTGSe, x ~ 0.5) thin films is studied. Kesterite layer is deposited by co-evaporation onto 5 × 5 cm2 Mo/SLG substrate followed by a thermal treatment at maximum temperature of 480 °C, obtaining areas with different composition and morphology which are due to the sample position in the co-evaporation system and to the non-uniform temperature distribution across the substrate. Kesterite layers with higher Zn amounts are characterized by lower Cu and Ge contents; however, a uniform Ge distribution through the absorber layer is detected in all cases. The excess Zn concentration leads to the formation of ZnSe secondary phase on the surface and in the bulk of the absorber as determined by Raman spectroscopy. When higher Ge content and no ZnSe are present in the absorber layer, a compact structure is formed with larger grain size of kesterite. This effect could explain the higher Voc of the solar cell. The Zn content does not affect the bandgap energy significantly (Eg near 1.3 eV), although the observed effect of Zn excess in CZTGSe results in a decreased device performance from 6.4 to 4.2%. This investigation reveals the importance of the control of the off-stoichiometric CZTGSe composition during the deposition process to enhance solar cells propertiesThis work was supported by Spanish Ministry of Science, Innovation and Universities Project WINCOST (ENE2016-80788-C5-2-R) and European Project INFINITE CELL (H2020-MSCA-RISE-2017-777968). ARP also acknowledges financial support from Community of Madrid within Youth Employment Program (PEJD-2017-PRE/IND-4062). MG acknowledges the financial support from ACCIÓ-Generalitat de Catalunya within the TECNIOspring Plus fellowship (TECSPR18-1-0048

Persistent recruitment of somatosensory cortex during active maintenance of hand images in working memory

Working memory (WM) supports temporary maintenance of task-relevant information. This process is associated with persistent activity in the sensory cortex processing the information (e.g., visual stimuli activate visual cortex). However, we argue here that more multifaceted stimuli moderate this sensory-locked activity and recruit distinctive cortices. Specifically, perception of bodies recruits somatosensory cortex (SCx) beyond early visual areas (suggesting embodiment processes). Here we explore persistent activation in processing areas beyond the sensory cortex initially relevant to the modality of the stimuli. Using visual and somatosensory evoked-potentials in a visual WM task, we isolated different levels of visual and somatosensory involvement during encoding of body and non-body-related images. Persistent activity increased in SCx only when maintaining body images in WM, whereas visual/posterior regions' activity increased significantly when maintaining non-body images. Our results bridge WM and embodiment frameworks, supporting a dynamic WM process where the nature of the information summons specific processing resources

Dance Expertise modulates behavioural and psychophysiological responses to affective body movement

The present study shows how motor expertise increases sensitivity to affective body movement at the behavioural and physiological level. Nineteen affective movement experts (professional ballet dancers) and twenty-four controls watched 96 video clips of emotionally expressive body movements while they performed an affect rating task (subjective response) and their galvanic skin response was recorded (psychophysiological response). The movements in the clips were either sad or happy, and in half of the trials movements were played in the order in which they are learned (forward presentation), and in the other half, backwards (control condition). Results showed that motor expertise in affective body movement specifically modulated both behavioural and physiological sensitivity to others’ affective body movement, and that this sensitivity is particularly strong when movements are shown in the way they are learnt (forward presentation). The evidence is discussed within current theories of proprioceptive arousal feedback and motor simulation accounts