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How Artificial Intelligence is Supporting Neuroscience Research: A Discussion About Foundations, Methods and Applications

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Computational Neuroscience (LAWCN 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 720))

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Abstract

The Artificial Intelligence (AI) research field has presented a considerable growth in the last decades, helping researchers to explore new possibilities into their works. Neuroscience’s studies are characterized for recording high dimensional and complex brain data, making the data analysis computationally expensive and time consuming. Neuroscience takes advantage of AI techniques and the increasing processing power in modern computers, which helped improving the understanding of brain behavior. This paper presents some AI techniques, focusing mainly in Deep Learning (DL), as a powerful tool for data analysis. The foundations and basic concepts of some DL models are presented in order to offer a brief understanding to scientists. Likewise, applications of these models on Neuroscience researches are also presented.

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Authors and Affiliations

  1. Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil

    Rafael T. Gonzalez, Jaime A. Riascos & Dante A. C. Barone

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  1. Rafael T. Gonzalez
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  2. Jaime A. Riascos
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  3. Dante A. C. Barone
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Correspondence to Rafael T. Gonzalez .

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Editors and Affiliations

  1. Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Dante Augusto Couto Barone

  2. Federal Institute of Education, Science and Technology of Bahia, Camacari, Brazil

    Eduardo Oliveira Teles

  3. Federal Institute of Education, Science and Technology Farroupilha, Santa Maria, Brazil

    Christian Puhlmann Brackmann

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Gonzalez, R.T., Riascos, J.A., Barone, D.A.C. (2017). How Artificial Intelligence is Supporting Neuroscience Research: A Discussion About Foundations, Methods and Applications. In: Barone, D., Teles, E., Brackmann, C. (eds) Computational Neuroscience. LAWCN 2017. Communications in Computer and Information Science, vol 720. Springer, Cham. https://doi.org/10.1007/978-3-319-71011-2_6

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  • DOI: https://doi.org/10.1007/978-3-319-71011-2_6

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