Cognición y representación interna de entornos dinámicos en el cerebro de los mamíferos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Biológicas, leída el 07/05/2021El tiempo es una de las dimensiones fundamentales de la realidad. Paradójicamente, los fenómenos temporales del mundo natural contienen ingentes cantidades de información redundante, y a pesar de ello, codificar internamente el tiempo en el cerebro es imprescindible para anticiparse a peligros en ambientes dinámicos. No obstante, dedicar grandes cantidades de recursos cognitivos a procesar las características espacio-temporales de entornos complejos debería ser incompatible con la supervivencia, que requiere respuestas rápidas. Aun así, los animales son capaces de tomar decisiones en intervalos de tiempo muy estrechos. ¿Cómo consigue hacer esto el cerebro? Como respuesta al balance entre complejidad y velocidad, la hipótesis de la compactación del tiempo propone que el cerebro no codifica el tiempo explícitamente, sino que lo integra en el espacio. En teoría, la compactación del tiempo simplifica las representaciones internas del entorno, reduciendo significativamente la carga de trabajo dedicada a la planificación y la toma de decisiones. La compactación del tiempo proporciona un marco operativo que pretende explicar cómo las situaciones dinámicas, percibidas o producidas, se representan cognitivamente en forma de predicciones espaciales o representaciones internas compactas (CIR), que pueden almacenarse en la memoria y recuperarse más adelante para generar respuestas. Aunque la compactación del tiempo ya ha sido implementada en robots, hasta ahora no se había comprobado su existencia como mecanismo biológico y cognitivo en el cerebro...Time is one of the most prominent dimensions that organize reality. Paradoxically, there are loads of redundant information contained within the temporal features of the natural world, and yet internal coding of time in the brain seems to be crucial for anticipating time-changing, dynamic hazards. Allocating such significant brain resources to process spatiotemporal aspects of complex environments should apparently be incompatible with survival, which requires fast and accurate responses. Nonetheless, animals make decisions under pressure and in narrow time windows. How does the brain achieve this? An effort to resolve the complexity-velocity trade-off led to a hypothesis called time compaction, which states the brain does not encode time explicitly but embeds it into space. Theoretically, time compaction can significantly simplify internal representations of the environment and hence ease the brain workload devoted to planning and decision-making. Time compaction also provides an operational framework that aims to explain how perceived and produced dynamic situations are cognitively represented, in the form of spatial predictions or compact internal representations (CIRs) that can be stored in memory and be used later on to guide behaviour and generate action. Although successfully implemented in robots, time compaction still lacked assessment of its biological soundness as an actual cognitive mechanism in the brain...Fac. de Ciencias BiológicasTRUEunpu

Analysis of the sexist representation of the figure of women: case study of the most viewed video clips on YouTube Spain in 2020

[ES] La figura de la mujer en los medios audiovisuales ha estado tradicionalmente asociada a una sobrexposición de sus atributos sexuales como objeto de deseo y no como sujeto deseante. Con el objetivo de analizar si esta tendencia sigue presente en los hábitos de consumo actuales, en este trabajo se presenta un estudio de casos para analizar los 10 videoclips más vistos en 2020 en YouTube España. Los resultados del análisis de los videoclips revelan que el uso de referentes sexuales y la representación del cuerpo de la mujer se alejan de la neutralidad. Además, la aparición de mujeres latinas y caucásicas de complexión ectomorfa se asoció con un mayor grado de sexismo. Esto revela que la tendencia sexista se mantiene en las preferencias de consumo de la sociedad española en cuanto a videoclip y letras de las canciones.[EN] The figure of women in the audiovisual media has traditionally been associated with an overexposure of their sexual attributes as an object of desire and not as a desiring subject. In order to analyze whether this trend is still present in current consumer habits, this work presents a case study to analyze the 10 most viewed video clips in 2020 on YouTube Spain. The results of the content analysis reveal that the use of sexual references and the representation of the woman's body are far from neutrality. In addition, the appearance of Latina and Caucasian women with an ectomorphic complexion was associated with a higher degree of sexism. This reveals that the sexist trend is maintained in the consumer preferences of Spanish society in terms of video clips and song lyrics

Characterization of Leptoglossus occidentalis eggs and egg glue

Producción CientíficaSimple Summary: This study explored the chemical components of the egg glue used by the Western Conifer Seed Bug (Leptoglossus occidentalis Heidemann, 1910) to agglutinate eggs and adhere to pine needles. Results showed that the adhesive secretion includes plasticizers and thermoplastic elastomer resins with semiochemical properties in an oily matrix containing proteins. This knowledge of the egg glue composition can be used to develop new control strategies for L. occidentalis, potentially limiting the economic impact caused by this pest insect that reduces the production of pine nuts by up to 25%.The western conifer seed bug (Leptoglossus occidentalis Heidemann, 1910, Heteroptera: Coreidae) has a significant economic impact due to the reduction in the quality and viability of conifer seed crops; it can feed on up to 40 different species of conifers, showing a clear predilection for Pinus pinea L. in Europe. Its incidence is especially relevant for the pine nut-producing industry, given that the action of this pest insect can reduce the production of pine nuts by up to 25%. As part of ongoing efforts aimed at the design of control strategies for this insect, this work focuses on the characterization (by scanning electron microscopy–energy-dispersive X-ray spectroscopy, Fourier-transform infrared spectroscopy, and gas chromatography–mass spectroscopy, GC–MS) of the compounds released by these insects during oviposition, with emphasis on the adhesive secretion that holds L. occidentalis eggs together. Elemental analysis pointed to the presence of significant amounts of compounds with high nitrogen content. Functional groups identified by infrared spectroscopy were compatible with the presence of chitin, scleroproteins, LNSP-like and gelatin proteins, shellac wax analogs, and policosanol. Regarding the chemical species identified by GC–MS, eggs and glue hydromethanolic extracts shared constituents such as butyl citrate, dibutyl itaconate, tributyl aconitate, oleic acid, oleamide, erucamide, and palmitic acid, while eggs also showed stearic and linoleic acid-related compounds. Knowledge of this composition may allow advances in new strategies to address the problem caused by L. occidentalis.Unión Europea, LIFE MycoRestore - (project LIFE18 CCA/ES/001110

Rain-fed granite rock basins accumulate a high diversity of dormant microbial eukaryotes

Rain fed granite rock basins are ancient geological landforms of worldwide distribution and structural simplicity. They support habitats that can switch quickly from terrestrial to aquatic along the year. Diversity of animals and plants, and the connexion between communities in different basins have been widely explored in these habitats, but hardly any research has been carried out on microorganisms. The aim of this study is to provide the first insights on the diversity of eukaryotic microbial communities from these environments. Due to the ephemeral nature of these aquatic environments, we predict that the granitic basins should host a high proportion of dormant microeukaryotes. Based on an environmental DNA diversity survey, we reveal diverse communities with representatives of all major eukaryotic taxonomic supergroups, mainly composed of a diverse pool of low abundance OTUs. Basin communities were very distinctive, with alpha and beta diversity patterns non-related to basin size or spatial distance respectively. Dissimilarity between basins was mainly characterised by turnover of OTUs. The strong microbial eukaryotic heterogeneity observed among the basins may be explained by a complex combination of deterministic factors (diverging environment in the basins), spatial constraints, and randomness including founder effects. Most interestingly, communities contain organisms that cannot coexist at the same time because of incompatible metabolic requirements, thus suggesting the existence of a pool of dormant organisms whose activity varies along with the changing environment. These organisms accumulate in the pools, which turns granitic rock into high biodiversity microbial islands whose conservation and study deserve further attention.Ministerio de Economía, Industria y Competitividad, Gobierno de Españ

Benchmarking of tools for axon length measurement in individually-labeled projection neurons

Projection neurons are the commonest neuronal type in the mammalian forebrain and their individual characterization is a crucial step to understand how neural circuitry operates. These cells have an axon whose arborizations extend over long distances, branching in complex patterns and/or in multiple brain regions. Axon length is a principal estimate of the functional impact of the neuron, as it directly correlates with the number of synapses formed by the axon in its target regions; however, its measurement by direct 3D axonal tracing is a slow and labor-intensive method. On the contrary, axon length estimations have been recently proposed as an effective and accessible alternative, allowing a fast approach to the functional significance of the single neuron. Here, we analyze the accuracy and efficiency of the most used length estimation tools—design-based stereology by virtual planes or spheres, and mathematical correction of the 2D projected-axon length—in contrast with direct measurement, to quantify individual axon length. To this end, we computationally simulated each tool, applied them over a dataset of 951 3D-reconstructed axons (from NeuroMorpho.org), and compared the generated length values with their 3D reconstruction counterparts. The evaluated reliability of each axon length estimation method was then balanced with the required human effort, experience and know-how, and economic affordability. Subsequently, computational results were contrasted with measurements performed on actual brain tissue sections. We show that the plane-based stereological method balances acceptable errors (~5%) with robustness to biases, whereas the projection-based method, despite its accuracy, is prone to inherent biases when implemented in the laboratory. This work, therefore, aims to provide a constructive benchmark to help guide the selection of the most efficient method for measuring specific axonal morphologies according to the particular circumstances of the conducted research

Machine learning regularity representation from biological patterns: a case study in a Drosophila neurodegenerative model

This work presents a fully automated classification pipeline of bright-field images based on HOG descriptors and machine learning techniques. An initial ROI extraction is performed applying TopHat morphological kernel and Euclidean distance to centroid thesholding. Image classification algorithms are trained on these ROIs (SVM, Decision Trees, Random Forest, CNN) and their performance is evaluated on independent, unseen datasets. HOG + gaussian kernel SVM (0.97 accuracy and 0.98 AUC) and fine-tune pre-trained CNN (0.98 accuracy and 0.99 AUC) yielded the best results overall.Con este trabajo se pretende proporcionar una herramienta totalmente automática de multiclasificación basada en la extracción de descriptores HOG y técnicas de deep learning. Se presenta un algoritmo de segmentación y extracción del ROI correspondiente al área del ojo, utilizando transformaciones morfológicas TopHat y filtraje por distancia al centroide del conjunto de píxels. Sobre estos ROIs se comparan diferentes algoritmos de clasificación (SVM, árboles de decisión, Random Forest)Amb aquest treball es pretén proporcionar una eina totalment automàtica de multiclasificación basada en l'extracció de descriptores HOG i tècniques de deep learning. Es presenta un algorisme de segmentació i extracció del ROI corresponent a l'àrea de l'ull, utilitzant transformacions morfològiques TopHat i filtratge per distància al centroide del conjunt de píxels. Sobre aquests ROIs es comparen diferents algorismes de classificació (SVM, arbres de decisió, Random Forest

Semantic Knowledge Representation for Strategic Interactions in Dynamic Situations

This work was supported by the Russian Science Foundation (project 19-12-00394) and by the Spanish Ministry of Science, Innovation and Universities (grant FIS2017-82900-P).Evolved living beings can anticipate the consequences of their actions in complex multilevel dynamic situations. This ability relies on abstracting the meaning of an action. The underlying brain mechanisms of such semantic processing of information are poorly understood. Here we show how our novel concept, known as time compaction, provides a natural way of representing semantic knowledge of actions in time-changing situations. As a testbed, we model a fencing scenario with a subject deciding between attack and defense strategies. The semantic content of each action in terms of lethality, versatility, and imminence is then structured as a spatial (static) map representing a particular fencing (dynamic) situation. The model allows deploying a variety of cognitive strategies in a fast and reliable way. We validate the approach in virtual reality and by using a real humanoid robot.Depto. de Análisis Matemático y Matemática AplicadaDepto. de Biodiversidad, Ecología y EvoluciónFac. de Ciencias BiológicasInstituto de Matemática Interdisciplinar (IMI)TRUEpu

Effects of Fasting and Feeding on Transcriptional and Posttranscriptional Regulation of Insulin-Degrading Enzyme in Mice

© 2021 by the authors.Insulin-degrading enzyme (IDE) is a highly conserved and ubiquitously expressed Zn2+-metallopeptidase that regulates hepatic insulin sensitivity, albeit its regulation in response to the fasting-to-postprandial transition is poorly understood. In this work, we studied the regulation of IDE mRNA and protein levels as well as its proteolytic activity in the liver, skeletal muscle, and kidneys under fasting (18 h) and refeeding (30 min and 3 h) conditions, in mice fed a standard (SD) or high-fat (HFD) diets. In the liver of mice fed an HFD, fasting reduced IDE protein levels (~30%); whereas refeeding increased its activity (~45%) in both mice fed an SD and HFD. Likewise, IDE protein levels were reduced in the skeletal muscle (~30%) of mice fed an HFD during the fasting state. Circulating lactate concentrations directly correlated with hepatic IDE activity and protein levels. Of note, L-lactate in liver lysates augmented IDE activity in a dose-dependent manner. Additionally, IDE protein levels in liver and muscle tissues, but not its activity, inversely correlated (R2 = 0.3734 and 0.2951, respectively; p < 0.01) with a surrogate marker of insulin resistance (HOMA index). Finally, a multivariate analysis suggests that circulating insulin, glucose, non-esterified fatty acids, and lactate levels might be important in regulating IDE in liver and muscle tissues. Our results highlight that the nutritional regulation of IDE in liver and skeletal muscle is more complex than previously expected in mice, and that fasting/refeeding does not strongly influence the regulation of renal IDE.This research was funded by Ministerio de Economía, Industria y Competitividad, grants numbers SAF2016-77871-C2-1-R to I.C.-C. and SAF2016-77871-C2-2-R to G.P. Ministerio de Ciencia e Innovación PID2019-110496RB-C21 to I.C.-C. and PID2019-110496RB-C22 to G.P.; European Foundation for the Study of Diabetes (European Diabetes Research Programme on New Targets for Type 2 Diabetes supported by MSD-2017) to I.C.-C. and G.P.; European Foundation for the Study of Diabetes Rising Star Fellowship Programme supported by EFSD-Novo Nordisk and Sociedad Española de Diabetes (SED) Young Basic Researchers grant to B.M.; and U.S. National Institutes of Health GM115617 to M.A.L. The project leading to these results has received funding from “La Caixa” Foundation, under agreement LCF/PR/PR18/51130007 to G.P. This research was funded by Programa Estratégico Instituto de Biología y Genética Molecular (IBGM), Escalera de Excelencia, Junta de Castilla y León (Ref. CLU-2019-02). C.M.G.-C. was supported by a fellowship from the Junta de Castilla y León and the European Social Fund (ORDER EDU/574/2018)

Static internal representation of dynamic situations reveals time compaction in human cognition

Introduction: The human brain has evolved under the constraint of survival in complex dynamic situations. It makes fast and reliable decisions based on internal representations of the environment. Whereas neural mechanisms involved in the internal representation of space are becoming known, entire spatiotemporal cognition remains a challenge. Growing experimental evidence suggests that brain mechanisms devoted to spatial cognition may also participate in spatiotemporal information processing. Objectives: The time compaction hypothesis postulates that the brain represents both static and dynamic situations as purely static maps. Such an internal reduction of the external complexity allows humans to process time-changing situations in real-time efficiently. According to time compaction, there may be a deep inner similarity between the representation of conventional static and dynamic visual stimuli. Here, we test the hypothesis and report the first experimental evidence of time compaction in humans. Methods: We engaged human subjects in a discrimination-learning task consisting in the classification of static and dynamic visual stimuli. When there was a hidden correspondence between static and dynamic stimuli due to time compaction, the learning performance was expected to be modulated. We studied such a modulation experimentally and by a computational model. Results: The collected data validated the predicted learning modulation and confirmed that time compaction is a salient cognitive strategy adopted by the human brain to process time-changing situations. Mathematical modelling supported the finding. We also revealed that men are more prone to exploit time compaction in accordance with the context of the hypothesis as a cognitive basis for survival. Conclusions: The static internal representation of dynamic situations is a human cognitive mechanism involved in decision-making and strategy planning to cope with time-changing environments. The finding opens a new venue to understand how humans efficiently interact with our dynamic world and thrive in nature