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Symbolic and non symbolic number processing a developmental perspective

The symbolic number system that has evolved in humans enables more complex and accurate calculations than a non-symbolic system. The application of this symbolic system has turned out to be so useful that we have a hard time imagi... ver más

31/03/2013

KU Leuven

159K€

Presupuesto del proyecto: 159K€

Líder del proyecto

KATHOLIEKE UNIVERSITEIT LEUVEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2013-03-31 No tenemos la información de la convocatoria

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KU Leuven

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Líder del proyecto

KATHOLIEKE UNIVERSITEIT LEUVEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 159K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The symbolic number system that has evolved in humans enables more complex and accurate calculations than a non-symbolic system. The application of this symbolic system has turned out to be so useful that we have a hard time imagining the world without it. This patent importance makes the study of questions about the acquisition and implementation of these processes in the human brain very relevant. In the current study, three important and related topics in numerical cognition will be addressed: (1) the neural mechanisms underlying the acquisition of symbolic and non-symbolic mathematical abilities in young children, (2) the possible predictive value of numerical abilities or their neural correlates in the acquisition of proficient symbolic mathematical abilities and (3) the neural mechanisms underlying typical and atypical mathematics development. To address these issues we will use both behavioral as well as imaging techniques: electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). These neuroimaging methods are complementary as they provide information about the timing of processes and the neural substrates subserving these processes, respectively. Moreover, besides the timing of processes, EEG can also be used to study neuronal coherence. For instance, frequency band analysis of EEG data has been proven to be of great value in studying cognitive maturation. This method, which has not been implemented in the field of numerical cognition yet, has great potential to advance this field of research. In conclusion, we will address questions question about the neural mechanisms involved in the development of numerical abilities using neuroimaging techniques. The outcomes can have major impact on the implementation of mathematics education and the early identification of children at risk for mathematical difficulties (also referred to as dyscalculia).

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