Domain specific traits predict achievement in music and multipotentiality

Previous research shows that individuals choose careers based on the relative strengths of various traits. More debated however, is how specific combinations of traits predict individual differences in professional achievements. General intelligence is often proposed to be the best predictor of eminence, but some studies suggest that more specific traits can be relatively important when performance depends on specific skills and expertise. Here we identified a comprehensive set of variables relevant for music achievement (intelligence, auditory ability, absolute pitch, Big-five personality traits, psychosis proneness, music flow proneness, childhood environment and music practice), and tested how they predicted level of musicianship (non-musicians vs. amateur musicians vs. professional musicians) and number of achievements among professional musicians. We used web survey data from a total of 2150 individuals, and generalized additive models that can also reveal non-linear relationships. The results largely confirmed our three main hypotheses: (i) non-musicians, amateur musicians, and professional musicians are best differentiated by domain specific abilities, personality traits, and childhood factors; (ii) largely the same significant predictors are also associated with the number of creative achievements within professional musicians; (iii) individuals who reach a professional level in two domains (here science and music) possess the union of the relevant traits of both domains. In addition, many of the associations between predictors and achievement were non-linear. This study confirms that in music, and potentially in other occupational fields where performance relies on specific competences, domain relevant characteristics may be better predictors of engagement and creative achievement than broad traits

Investigating the relationship between childhood music practice and pitch-naming ability in professional musicians and a population-based twin sample

The relationship between pitch-naming ability and childhood onset of music training is well established and thought to reflect both genetic predisposition and music training during a critical period. However, the importance of the amount of practice during this period has not been investigated. In a population sample of twins (N = 1447, 39% male, 367 complete twin pairs) and a sample of 290 professional musicians (51% male), we investigated the role of genes, age of onset of playing music and accumulated childhood practice on pitch-naming ability. A significant correlation between pitch-naming scores for monozygotic (r = .27, p < .001) but not dizygotic twin pairs (r = −.04, p = .63) supported the role of genetic factors. In professional musicians, the amount of practice accumulated between ages 6 and 11 predicted pitch-naming accuracy (p = .025). In twins, age of onset was no longer a significant predictor once practice was considered. Combined, these findings are in line with the notion that pitch-naming ability is associated with both genetic factors and amount of early practice, rather than just age of onset per se. This may reflect a dose–response relation between practice and pitch-naming ability in genetically predisposed individuals. Alternatively, children who excel at pitch-naming may have an increased tendency to practice

The Swedish Twin Registry : establishment of a biobank and other recent developments

The Swedish Twin Registry (STR) today contains more than 194,000 twins and more than 75,000 pairs have zygosity determined by an intra-pair similarity algorithm, DNA, or by being of opposite sex. Of these, approximately 20,000, 25,000, and 30,000 pairs are monozygotic, same-sex dizygotic, and opposite-sex dizygotic pairs, respectively. Since its establishment in the late 1950s, the STR has been an important epidemiological resource for the study of genetic and environmental influences on a multitude of traits, behaviors, and diseases. Following large investments in the collection of biological specimens in the past 10 years we have now established a Swedish twin biobank with DNA from 45,000 twins and blood serum from 15,000 twins, which effectively has also transformed the registry into a powerful resource for molecular studies. We here describe the main projects within which the new collections of both biological samples as well as phenotypic measures have been collected. Coverage by year of birth, zygosity determination, ethnic heterogeneity, and influences of in vitro fertilization are also described.VetenskapsrådetNIHSSFHjärt- och LungfondenAstma- och AllergiförbundetAccepte

Neuron-glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Junior Leader Fellowship Program by “la Caixa” Banking Foundation (LCF/BQ/LI18/11630006

Development and Validation of the Computerised Adaptive Beat Alignment Test (CA-BAT)

Beat perception is increasingly being recognised as a fundamental musical ability. A number of psychometric instruments have been developed to assess this ability, but these tests do not take advantage of modern psychometric techniques, and rarely receive systematic validation. The present research addresses this gap in the literature by developing and validating a new test, the Computerised Adaptive Beat Alignment Test (CA-BAT), a variant of the Beat Alignment Test (BAT) that leverages recent advances in psychometric theory, including item response theory, adaptive testing, and automatic item generation. The test is constructed and validated in four empirical studies. The results support the reliability and validity of the CA-BAT for laboratory testing, but suggest that the test is not well-suited to online testing, owing to its reliance on fne perceptual discrimination

Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation

Modern psychometric theory provides many useful tools for ability testing, such as item response theory, computerised adaptive testing, and automatic item generation. However, these techniques have yet to be integrated into mainstream psychological practice. This is unfortunate, because modern psychometric techniques can bring many benefits, including sophisticated reliability measures, improved construct validity, avoidance of exposure effects, and improved efficiency. In the present research we therefore use these techniques to develop a new test of a well-studied psychological capacity: melodic discrimination, the ability to detect differences between melodies. We calibrate and validate this test in a series of studies. Studies 1 and 2 respectively calibrate and validate an initial test version, while Studies 3 and 4 calibrate and validate an updated test version incorporating additional easy items. The results support the new test’s viability, with evidence for strong reliability and construct validity. We discuss how these modern psychometric techniques may also be profitably applied to other areas of music psychology and psychological science in general

Neuron-Glial Interactions

Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Comment: 43 pages, 2 figures, 1 table. Accepted for publication in the "Encyclopedia of Computational Neuroscience," D. Jaeger and R. Jung eds., Springer-Verlag New York, 2020 (2nd edition

A Neuron-Glial Perspective for Computational Neuroscience

International audienceThere is growing excitement around glial cells, as compelling evidence point to new, previously unimaginable roles for these cells in information processing of the brain, with the potential to affect behavior and higher cognitive functions. Among their many possible functions, glial cells could be involved in practically every aspect of the brain physiology in health and disease. As a result, many investigators in the field welcome the notion of a Neuron-Glial paradigm of brain function, as opposed to Ramon y Cayal's more classical neuronal doctrine which identifies neurons as the prominent, if not the only, cells capable of a signaling role in the brain. The demonstration of a brain-wide Neuron-Glial paradigm however remains elusive and so does the notion of what neuron-glial interactions could be functionally relevant for the brain computational tasks. In this perspective, we present a selection of arguments inspired by available experimental and modeling studies with the aim to provide a biophysical and conceptual platform to computational neuroscience no longer as a mere prerogative of neuronal signaling but rather as the outcome of a complex interaction between neurons and glial cells