Why do spatial abilities predict mathematical performance?

Spatial ability predicts performance in mathematics and eventual expertise in science, technology and engineering. Spatial skills have also been shown to rely on neuronal networks partially shared with mathematics. Understanding the nature of this association can inform educational practices and intervention for mathematical underperformance. Using data on two aspects of spatial ability and three domains of mathematical ability from 4174 pairs of 12-year-old twins, we examined the relative genetic and environmental contributions to variation in spatial ability and to its relationship with different aspects of mathematics. Environmental effects explained most of the variation in spatial ability (~70%) and in mathematical ability (~60%) at this age, and the effects were the same for boys and girls. Genetic factors explained about 60% of the observed relationship between spatial ability and mathematics, with a substantial portion of the relationship explained by common environmental influences (26% and 14% by shared and non-shared environments respectively). These findings call for further research aimed at identifying specific environmental mediators of the spatial–mathematics relationship

Neural scaling laws for an uncertain world

Autonomous neural systems must efficiently process information in a wide range of novel environments, which may have very different statistical properties. We consider the problem of how to optimally distribute receptors along a one-dimensional continuum consistent with the following design principles. First, neural representations of the world should obey a neural uncertainty principle---making as few assumptions as possible about the statistical structure of the world. Second, neural representations should convey, as much as possible, equivalent information about environments with different statistics. The results of these arguments resemble the structure of the visual system and provide a natural explanation of the behavioral Weber-Fechner law, a foundational result in psychology. Because the derivation is extremely general, this suggests that similar scaling relationships should be observed not only in sensory continua, but also in neural representations of ``cognitive' one-dimensional quantities such as time or numerosity

Scientist - performers - audiences. Different modes of meaning-making

This paper provides a brief overview of the emergence of dance in the field of cognitive neuroscience and sustains the importance to understand-ing how dance is conceptualised in other disciplines in order to design valuable future research employing dance. It is proposed that recognising the distinct modes of meaning-making will undoubtedly affect and advance the scientific progress understanding by modes of meaning-making the phenomenological difference in how a dancer relates to a movement phrase from how a scientist or a choreographer watches, interprets, and experiences a dance phrase. The overall message is that the different modes of meaning-making requires consideration in scientific studies where a new generation of artists-scientists is needed, driven to excel in both, data handling and artistic purposes.//Abstract in Spanish:Este artículo proporciona una breve descripción de la aparición de la danza en el campo de la neurociencia cognitiva y sostiene que es importante entender cómo se conceptualiza la danza en otras disciplinas para diseñar in-vestigaciones futuras que la empleen. Se propone que reconocer los distintos modos de creación de significado afectará y avanzará el progreso científico entendiendo por modos de creación de significado la diferencia fenomenológica en la forma en que un bailarín se relaciona con una frase de movimiento de cómo lo hace un científico o un coreógrafo. El mensaje general es que los dif-erentes modos de creación de significado requieren consideración en estudios científicos donde son necesarios una nueva generación de artistas-científicos, impulsados a sobresalir tanto en el manejo de datos como en los propósitos artísticos

Computer Simulation of Musical Evolution: A Lesson from Whales

Simulating musical creativity using computers needs more than the ability to devise elegant computational implementations of sophisticated algorithms. It requires, firstly, an understanding of what phenomena might be regarded as music; and, secondly, an understanding of the nature of such phenomena — including their evolutionary history, their recursive-hierarchic structure, and the mechanisms by which they are transmitted within cultural groups. To understand these issues it is fruitful to compare human music, and indeed human language, with analogous phenomena in other areas of the animal kingdom. Whale song, specifically that of the humpback (Megaptera novaeangeliae), possesses many structural and functional similarities to human music (as do certain types of birdsong). Using a memetic perspective, this paper compares the “musilanguage” of humpbacks with the music of humans, and aims to identify a number of shared characteristics. A consequence of nature and nurture, these commonalities appear to arise partly from certain constraints of perception and cognition (and thus they determine an aspect of the environment within which the “musemes” (musical memes) constituting whale vocalizations and human music is replicated), and partly from the social-emotive-embodied and sexual-selective nature of musemic transmission. The paper argues that Universal-Darwinian forces give rise to uniformities of structure in phenomena we might regard as “music”, irrespective of the animal group — certain primates, cetaceans or birds - within which it occurs. It considers the extent to which whale song might be regarded as creative, by invoking certain criteria used to assess this attribute in human music. On the basis of these various comparisons, the paper concludes by attempting to draw conclusions applicable to those engaged in designing evolutionary music simulation/generation algorithms

Toward a General-Purpose Heterogeneous Ensemble for Pattern Classification

We perform an extensive study of the performance of different classification approaches on twenty-five datasets (fourteen image datasets and eleven UCI data mining datasets). The aim is to find General-Purpose (GP) heterogeneous ensembles (requiring little to no parameter tuning) that perform competitively across multiple datasets. The state-of-the-art classifiers examined in this study include the support vector machine, Gaussian process classifiers, random subspace of adaboost, random subspace of rotation boosting, and deep learning classifiers. We demonstrate that a heterogeneous ensemble based on the simple fusion by sum rule of different classifiers performs consistently well across all twenty-five datasets. The most important result of our investigation is demonstrating that some very recent approaches, including the heterogeneous ensemble we propose in this paper, are capable of outperforming an SVM classifier (implemented with LibSVM), even when both kernel selection and SVM parameters are carefully tuned for each dataset

The Boy Who Grew a New Brain: Understanding this Miracle from a Neuro-Quantum Perspective

In this paper, we present a case of a boy – Noah Wall, who till today surprises the world of neuroscience with his will to grow his brain and survive. The case presented in this study sets a stepping stone in understanding the advent of the will to make a choice, from a neuro-quantum mechanics interpretation. We propose that besides our internal states of choices (neurogenesis, neuroplasticity, cell differentiation, etc.) we also relate with external states of choices (love, compassion, empathy, emotions, etc.) that contributes to its emergence. Quantum uncertainty seems to support the existence of a fundamental property based on which the universe functions; which means that even the nothing of free space has a small chance of containing something. Outcomes are not determined by prior or random events but by consciousness that gives rise to these outcomes. This provides us a lead into understanding the existence of the will and the origin of choice when we look deeper into the realms of the implausible interpretations of quantum mechanics. Free will is the ability for the mind to choose between possible outcomes. Willful power is therefore not only a psychological intervention but also a biological and quantum intervention, where we have the capacity to make choices about what direction we will take, making a change to the systematic functioning of our body