The latency-amplitude binomial of waves resulting from the application of evoked potentials for the diagnosis of dyscalculia
Document typeConference report
PublisherWorld Academy of Science, Engineering and Technology (WASET)
Rights accessOpen Access
Recent advances in cognitive neuroscience have allowed a step forward in perceiving the processes involved in learning from the point of view of acquiring new information or the modification of existing mental content. The evoked potentials technique reveals how basic brain processes interact to achieve adequate and flexible behaviours. The objective of this work, using evoked potentials, is to study if it is possible to distinguish if a patient suffers a specific type of learning disorder to decide the possible therapies to follow. The methodology used in this work is to analyze the dynamics of different brain areas during a cognitive activity to find the relationships between the other areas analyzed to understand the functioning of neural networks better. Also, the latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of non-invasive, innocuous, low-cost and easy-access techniques such as, among others, the evoked potentials that can help to detect early possible neurodevelopmental difficulties for their subsequent assessment and therapy. From the study of the amplitudes and latencies of the evoked potentials, it is possible to detect brain alterations in the learning process, specifically in dyscalculia, to achieve specific corrective measures for the application of personalized psycho-pedagogical plans that allow obtaining an optimal integral development of the affected people.
CitationGarcia-Planas, M.I.; García-Camba, M. The latency-amplitude binomial of waves resulting from the application of evoked potentials for the diagnosis of dyscalculia. A: International Conference on Learning Disabilities and Disorders. "XV. international research conference proceedings". Riverside, Connecticut: World Academy of Science, Engineering and Technology (WASET), 2021, p. 119-123. ISBN 1307-6892.