Reduced kinetic models of facilitative transport

AbstractIn spite of the highly complex structural dynamics of globular proteins, the processes mediated by them can usually be described in terms of relatively simple kinetic diagrams. How do complex proteins, characterized by undergoing transitions among a possibly very large number of intermediate states, exhibit functional properties that can be interpreted in terms of kinetic diagrams consisting of only a small number of states? One possible way of explaining this apparent contradiction is that, under some conditions, a reduction of the actual complete kinetic diagram that describes all of the macromolecular states and transitions takes place. In this work, we contribute with a formal basis to this interpretation, by generalizing the procedure of diagram reduction to the case of multicyclic kinetic diagrams. As an example, we apply the procedure to a complex kinetic model of facilitative transport. We develop Monte Carlo simulations to obtain the kinetic parameters of the complex model and we compare them with the ones analytically obtained from the reduced model. We confirm that, under some conditions, the kinetic behavior of the complex transporter is indistinguishable from the one of a four-state simple carrier model, derived from the former by diagram reduction. Besides introducing some novel methodological aspects, this work further contributes to the idea that, under many physiological and experimental conditions, a reduction occurs of the complete kinetic diagram that describes the dynamics of a globular protein

Teaching the science in neuroscience to protect from neuromyths: from courses to fieldwork

In recent decades, Cognitive Neuroscience has evolved from a rather arcane field trying to understand how the brain supports mental activities, to one that contributes to public policies. In this article, we focus on the contributions from Cognitive Neuroscience to Education. This line of research has produced a great deal of information that can potentially help in the transformation of Education, promoting interventions that help in several domains including literacy and math learning, social skills and science. The growth of the Neurosciences has also created a public demand for knowledge and a market for neuro-products to fulfill these demands, through books, booklets, courses, apps and websites. These products are not always based on scientific findings and coupled to the complexities of the scientific theories and evidence, have led to the propagation of misconceptions and the perpetuation of neuromyths. This is particularly harmful for educators because these misconceptions might make them abandon useful practices in favor of others not sustained by evidence. In order to bridge the gap between Education and Neuroscience, we have been conducting, since 2013, a set of activities that put educators and scientists to work together in research projects. The participation goes from discussing the research results of our projects to being part and deciding aspects of the field interventions. Another strategy consists of a course centered around the applications of Neuroscience to Education and their empirical and theoretical bases. These two strategies have to be compared to popularization efforts that just present Neuroscientific results. We show that the more the educators are involved in the discussion of the methodological bases of Neuroscientific knowledge, be it in the course or as part of a stay, the better they manage the underlying concepts. We argue that this is due to the understanding of scientific principles, which leads to a more profound comprehension of what the evidence can and cannot support, thus shielding teachers from the false allure of some commercial neuro-products. We discuss the three approaches and present our efforts to determine whether they lead to a strong understanding of the conceptual and empirical base of Neuroscience.ANII: FSED-2- 13882

Detecting order-disorder transitions in discourse : implications for schizophrenia

Abstract Several psychiatric and neurological conditions affect the semantic organization and content of a patient's speech. Specifically, the discourse of patients with schizophrenia is frequently characterized as lacking coherence. The evaluation of disturbances in discourse is often used in diagnosis and in assessing treatment efficacy, and is an important factor in prognosis. Measuring these deviations, such as “loss of meaning” and incoherence, is difficult and requires substantial human effort. Computational procedures can be employed to characterize the nature of the anomalies in discourse. We present a set of new tools derived from network theory and information science that may assist in empirical and clinical studies of communication patterns in patients, and provide the foundation for future automatic procedures. First we review information science and complex network approaches to measuring semantic coherence, and then we introduce a representation of discourse that allows for the computation of measures of disorganization. Finally we apply these tools to speech transcriptions from patients and a healthy participant, illustrating the implications and potential of this novel framework

Lexiland: A Tablet-based Universal Screener for Reading Difficulties in the School Context

First published online January 27, 2022Massive and timely screening of the student population for early signs of reading difficulties is needed to implement timely effective remediation of these difficulties. However, traditional approaches are costly and hard to apply. Here, we present Lexiland, a tablet-based reading assessment tool for kindergarten and primary school children developed to be applied in school settings with minimal personnel intervention. Following a story line, players help a character of the game perform several tasks that measure different predictors of reading outcomes. Most of the tasks that usually involve a verbal response were switched to receptive tasks to demand a touch-screen response only. The tablet application was administered to a sample of N = 616 5-yo kindergarten children and to a sub-sample of these children twice during the following two years (First and Second Grades). Applying logistic regression and cross-validation, we selected a reduced subset of tasks that can predict with great sensitivity and specificity, whether a five-year-old child will have reading difficulties by the end of first grade (sensitivity 90% and specificity 76%) and two years later (sensitivity 90% and specificity 61%). Importantly, Lexiland is a scalable tool to implement universal screening, given the increasing availability of devices able to run android and iOS applications.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was funded by ANII FSED_2_2015_1_120741 and ANII FSED_2_2016_1_131230 grants to Juan Valle-Lisboa and Manuel Carreiras. Camila Zugarramurdi received a PhD Scholarship from Fundación Carolin

Mind the Orthography: Revisiting the Contribution of Prereading Phonological Awareness to Reading Acquisition

published Online First March 21, 2022.Reading acquisition is based on a set of preliteracy skills that lay the foundation for future reading abilities. Phonological awareness—the ability to identify and manipulate the sound units of oral language— has been reported to play a central role in reading acquisition. However, current evidence is mixed with respect to its universal contribution to reading acquisition across orthographies. This longitudinal study examines the development and contribution of phonological awareness to early reading skills in Spanish, a transparent orthography. The results of a comprehensive battery of phonological awareness skills in a large sample of children (Time 1 n = 616, 296 females, mean age 5.6, from middle to high socioeconomic backgrounds; Time 2 n = 397) with no reading experience at study onset suggest that the development of phonological awareness is delayed in Spanish. Furthermore, our results show that phonological awareness does not contribute to the prediction of reading acquisition above and beyond other preliteracy skills. Letter knowledge indexes children’s ability to identify phonemes and thus takes a more central role in the prediction of early reading skills. Therefore, we underscore the need to thoughtfully address the distinctive features of the reading acquisition process across orthographies, which should be taken into account in models of reading and learning to read.This project was funded by ANII FSED_2_2015_1_120741 and ANII FSED_2_2016_1_131230 Grants. Camila Zugarramurdi received a PhD Scholarship from Fundación Carolina

Diseño de una evaluación digitalizada de predictores de las dificultades lectoras

El presente proyecto se enfocó en implementar una batería digitalizada de tareas que permitiera evaluar predictores de dificultades en la lectura. Se basa, por un lado, en aportes ya clásicos de la Psicología Cognitiva y por otro en teorías recientes de la Neurociencia Cognitiva. Los aportes clásicos indican que es posible predecir dificultades en la lectura previamente a la instrucción lectora, principalmente a través de la evaluación de tres variables cognitivas: la conciencia fonológica, el conocimiento de las letras y la denominación rápida automatizada. Las evidencias provenientes de las Neurociencias Cognitivas sugieren que algunas de las dificultades en la lectura pueden explicarse por un pobre acoplamiento entre oscilaciones cerebrales y el ritmo presente en el lenguaje hablado, y que este acoplamiento puede ser medido comportamentalmente. Partiendo de esta base, nos planteamos la realización de un estudio longitudinal en dos tiempos que mida el desarrollo de estos constructos, previamente a la instrucción lectora y lo vincule con el desempeño lector 18 meses más tarde.Fundación Ceibal, Agencia Nacional de Investigación e Innovación (ANII

Representações sociais sobre a permanência na docência: o que dizem docentes do ensino fundamental?

Resumo Este estudo objetivou analisar as representações sociais de professores do ensino fundamental de escolas públicas sobre a sua permanência na docência na perspectiva das objetivações e ancoragens que organizam essas representações. A metodologia seguida consistiu na pesquisa de caráter descritivo e analítico com referência na Teoria das Representações Sociais. A amostra envolveu 25 professores dos sexos feminino e masculino que trabalham no ensino fundamental. O instrumento utilizado para a coleta de informações seguiu a técnica Q que consistiu na ordenação de setenta itens pré-elaborados sobre a temática em estudo para serem organizados por ordem de importância de acordo com cada informante. A análise das informações dos professores após registro seguiu os procedimentos da referida técnica, baseado no desvio padrão. Os resultados deste estudo destacam que as representações sociais de professores sobre a permanência na docência se organizam da seguinte forma: os docentes do grupo 1 selecionaram frases com sentidos desmotivadores para a permanência na profissão docente. Enquanto que os motivos que os docentes do grupo 2 elegem frases que expressam elementos motivadores para a permanência na docência. Conclui-se que existem polaridades entre as objetivações e as ancoragens nas representações sociais desses professores. As imagens tecidas sobre a profissão de professor editam uma profissão prazerosa, enquanto que os sentidos atribuídos são desprazerosos e desmotivadores para a permanência na profissão

The relative amount of information contributed by learning and bypre-specification in a SRN trained to compute sameness

We analyze the conditions under which Simple Recurrent Networks learn and generalize sameness. This task is difficultfor a generic SRN, and several properties of the network have to be established previous to any learning for generalizationto occur. We show that by selecting a set of narrow weight intervals a network can learn sameness from a limited set ofexamples. The intervals depend on the particular training set, and we obtained them from a series of simulations usingthe complete training set. We can approximate the relative amount of information provided by the initial structure andthe amount provided by the examples. Although we did not arrive to a general rule, in all our cases the initial structureprovides much more information than the examples. This shows that if something similar to ANN operates in the brain, arich innate structure is needed to support the learning of general functions

Simulations and theory of generalization in recurrent networks

Despite the tremendous advances of Artificial Intelligence, a general theory of intelligent systems, connecting the psycho-logical, neuroscientific and computational levels is lacking. Artificial Neural Networks are good starting points to buildthe theory. We propose to analyze generalization of learning in simple but challenging problems. We have previouslyproposed to concentrate on learning sameness, as we have shown that this is difficult for a SRN. Here we present theresults of trying to use a Long-Short Term Memory Network to learn sameness. We show that the LSTM although muchmore efficient to learn partial examples of sameness fails to generalize to a proportion of the examples. This suggests thatLSTM and SRN share a core set of features that make generalization of sameness problematic. By analyzing where thetwo models fail, we arrive at a proposal of what makes sameness hard to learn and generalize in recurrent neural networks